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Review/Check GGUF files and estimate the memory usage and maximum tokens per second.

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GGUF Parser

tl;dr, Review/Check GGUF files and estimate the memory usage.

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GGUF is a file format for storing models for inference with GGML and executors based on GGML. GGUF is a binary format that is designed for fast loading and saving of models, and for ease of reading. Models are traditionally developed using PyTorch or another framework, and then converted to GGUF for use in GGML.

GGUF Parser helps in reviewing and estimating the usage and maximum tokens per second of a GGUF format model without download it.

Key Features

  • No File Required: GGUF Parser uses chunking reading to parse the metadata of remote GGUF file, which means you don't need to download the entire file and load it.
  • Accurate Prediction: The evaluation results of GGUF Parser usually deviate from the actual usage by about 100MiB.
  • Quick Verification: You can provide device metrics to calculate the maximum tokens per second (TPS) without running the model.
  • Type Screening: GGUF Parser can distinguish what the GGUF file used for, such as Embedding, Reranking, LoRA, etc.
  • Fast: GGUF Parser is written in Go, which is fast and efficient.

Agenda

Notes

  • Since v0.13.0 (BREAKING CHANGE), GGUF Parser can parse files for StableDiffusion.Cpp or StableDiffusion.Cpp like application.
  • Experimentally, GGUF Parser can estimate the maximum tokens per second(MAX TPS) for a (V)LM model according to the --device-metric options.
  • GGUF Parser distinguishes the remote devices from --tensor-split via --rpc.
    • For one host multiple GPU devices, you can use --tensor-split to get the estimated memory usage of each GPU.
    • For multiple hosts multiple GPU devices, you can use --tensor-split and --rpc to get the estimated memory usage of each GPU. Since v0.11.0, --rpc flag masks the devices specified by --tensor-split in front.
  • Table result usage:
    • DISTRIBUTABLE indicates the GGUF file supports distribution inference or not, if the file doesn't support distribution inference, you can not offload it with RPC servers.
    • RAM indicates the system memory usage.
    • VRAM * indicates the local GPU memory usage.
    • RPC * (V)RAM indicates the remote memory usage. The kind of memory is determined by which backend the RPC server uses, check the running logs for more details.
    • UMA indicates the memory usage of Apple macOS only. NONUMA adapts to other cases, including none GPU devices.
    • LAYERS(I/T/O) indicates the count for input layers, transformer layers, and output layers. Input layers are not offloaded at present.

Installation

Install from releases.

Overview

Parse

Parse Local File

$ gguf-parser --path="~/.cache/lm-studio/models/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF/Hermes-2-Pro-Mistral-7B.Q5_K_M.gguf"
+-------------------------------------------------------------------------------------------+
| METADATA                                                                                  |
+-------+-------+-------+----------------+---------------+----------+------------+----------+
|  TYPE |  NAME |  ARCH |  QUANTIZATION  | LITTLE ENDIAN |   SIZE   | PARAMETERS |    BPW   |
+-------+-------+-------+----------------+---------------+----------+------------+----------+
| model | jeffq | llama | IQ3_XXS/Q5_K_M |      true     | 4.78 GiB |   7.24 B   | 5.67 bpw |
+-------+-------+-------+----------------+---------------+----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      32768      |      4096     |       4       |       true       |         32         |   32   |       14336      |      0     |      32032     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| llama |  450.50 KiB |    32032   |        N/A       |     1     |   32000   |    N/A    |    N/A    |      N/A      |       N/A       |      N/A      |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                      |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+-------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                VRAM 0               |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+--------+-----------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |   NONUMA  |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+
| llama |     32768    |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |   Supported   |   33 (32 + 1)  |       Yes      |      1 + 0 + 0     | 168.25 MiB | 318.25 MiB |     32 + 1     |  4 GiB | 11.16 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+

$ # Retrieve the model's metadata via split file,
$ # which needs all split files has been downloaded.
$ gguf-parser --path="~/.cache/lm-studio/models/Qwen/Qwen2-72B-Instruct-GGUF/qwen2-72b-instruct-q6_k-00001-of-00002.gguf"

+------------------------------------------------------------------------------------------------------------+
| METADATA                                                                                                   |
+-------+-------------------------+-------+--------------+---------------+-----------+------------+----------+
|  TYPE |           NAME          |  ARCH | QUANTIZATION | LITTLE ENDIAN |    SIZE   | PARAMETERS |    BPW   |
+-------+-------------------------+-------+--------------+---------------+-----------+------------+----------+
| model | 72b.5000B--cmix31-ba... | qwen2 |  IQ1_S/Q6_K  |      true     | 59.92 GiB |   72.71 B  | 7.08 bpw |
+-------+-------------------------+-------+--------------+---------------+-----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      32768      |      8192     |       8       |       true       |         64         |   80   |       29568      |      0     |     152064     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
|  gpt2 |   2.47 MiB  |   152064   |        N/A       |   151643  |   151645  |    N/A    |    N/A    |      N/A      |       N/A       |     151643    |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                      |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+-------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                VRAM 0               |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+--------+-----------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |   NONUMA  |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+
| qwen2 |     32768    |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |  Unsupported  |   81 (80 + 1)  |       Yes      |      1 + 0 + 0     | 291.38 MiB | 441.38 MiB |     80 + 1     | 10 GiB | 73.47 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+

Parse Remote File

$ gguf-parser --url="https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO-GGUF/resolve/main/Nous-Hermes-2-Mixtral-8x7B-DPO.Q3_K_M.gguf"
+------------------------------------------------------------------------------------------+
| METADATA                                                                                 |
+-------+----------+-------+--------------+---------------+--------+------------+----------+
|  TYPE |   NAME   |  ARCH | QUANTIZATION | LITTLE ENDIAN |  SIZE  | PARAMETERS |    BPW   |
+-------+----------+-------+--------------+---------------+--------+------------+----------+
| model | emozilla | llama |  Q4_K/Q3_K_M |      true     | 21 GiB |   46.70 B  | 3.86 bpw |
+-------+----------+-------+--------------+---------------+--------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      32768      |      4096     |       4       |       true       |         32         |   32   |       14336      |      8     |      32002     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| llama |  449.91 KiB |    32002   |        N/A       |     1     |   32000   |    N/A    |    N/A    |       0       |       N/A       |       2       |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                           |
+-------+--------------+--------------------+-----------------+-------------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+----------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION |  MMAP LOAD  | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                 VRAM 0                 |
|       |              |                    |                 |             |                |             |               |                |                +--------------------+------------+------------+----------------+-----------+-----------+
|       |              |                    |                 |             |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |    UMA    |   NONUMA  |
+-------+--------------+--------------------+-----------------+-------------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+-----------+-----------+
| llama |     32768    |     2048 / 512     |     Disabled    | Unsupported |       No       | Unsupported |   Supported   |   33 (32 + 1)  |       Yes      |      1 + 0 + 0     | 269.10 MiB | 419.10 MiB |     32 + 1     | 24.94 GiB | 27.41 GiB |
+-------+--------------+--------------------+-----------------+-------------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+-----------+-----------+

$ # Retrieve the model's metadata via split file

$ gguf-parser --url="https://huggingface.co/MaziyarPanahi/Meta-Llama-3.1-405B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-405B-Instruct.Q2_K.gguf-00001-of-00009.gguf"
+-------------------------------------------------------------------------------------------------------------+
| METADATA                                                                                                    |
+-------+-------------------------+-------+--------------+---------------+------------+------------+----------+
|  TYPE |           NAME          |  ARCH | QUANTIZATION | LITTLE ENDIAN |    SIZE    | PARAMETERS |    BPW   |
+-------+-------------------------+-------+--------------+---------------+------------+------------+----------+
| model | Models Meta Llama Me... | llama |     Q2_K     |      true     | 140.81 GiB |  410.08 B  | 2.95 bpw |
+-------+-------------------------+-------+--------------+---------------+------------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      131072     |     16384     |       8       |       true       |         128        |   126  |       53248      |      0     |     128256     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
|  gpt2 |    2 MiB    |   128256   |        N/A       |   128000  |   128009  |    N/A    |    N/A    |      N/A      |       N/A       |      N/A      |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                        |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+---------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                 VRAM 0                |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+---------+------------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA   |   NONUMA   |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+---------+------------+
| llama |    131072    |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |   Supported   |  127 (126 + 1) |       Yes      |      1 + 0 + 0     | 652.53 MiB | 802.53 MiB |     126 + 1    | 126 GiB | 299.79 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+---------+------------+

Parse From HuggingFace

Note

Allow using HF_ENDPOINT to override the default HuggingFace endpoint: https://huggingface.co.

$ gguf-parser --hf-repo="openbmb/MiniCPM-Llama3-V-2_5-gguf" --hf-file="ggml-model-Q5_K_M.gguf" --hf-mmproj-file="mmproj-model-f16.gguf"
+-------------------------------------------------------------------------------------------+
| METADATA                                                                                  |
+-------+-------+-------+----------------+---------------+----------+------------+----------+
|  TYPE |  NAME |  ARCH |  QUANTIZATION  | LITTLE ENDIAN |   SIZE   | PARAMETERS |    BPW   |
+-------+-------+-------+----------------+---------------+----------+------------+----------+
| model | model | llama | IQ3_XXS/Q5_K_M |      true     | 5.33 GiB |   8.03 B   | 5.70 bpw |
+-------+-------+-------+----------------+---------------+----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|       8192      |      4096     |       4       |       true       |         32         |   32   |       14336      |      0     |     128256     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
|  gpt2 |    2 MiB    |   128256   |        N/A       |   128000  |   128001  |    N/A    |    N/A    |     128002    |       N/A       |       0       |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                     |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |               VRAM 0               |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+--------+----------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |  NONUMA  |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+----------+
| llama |     8192     |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |   Supported   |   33 (32 + 1)  |       Yes      |      1 + 0 + 0     | 176.85 MiB | 326.85 MiB |     32 + 1     |  1 GiB | 7.78 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+----------+

$ # Retrieve the model's metadata via split file

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf"
+------------------------------------------------------------------------------------------------------------+
| METADATA                                                                                                   |
+-------+-------------------------+-------+--------------+---------------+-----------+------------+----------+
|  TYPE |           NAME          |  ARCH | QUANTIZATION | LITTLE ENDIAN |    SIZE   | PARAMETERS |    BPW   |
+-------+-------------------------+-------+--------------+---------------+-----------+------------+----------+
| model | Meta-Llama-3.1-405B-... | llama |     IQ1_M    |      true     | 88.61 GiB |  410.08 B  | 1.86 bpw |
+-------+-------------------------+-------+--------------+---------------+-----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      131072     |     16384     |       8       |       true       |         128        |   126  |       53248      |      0     |     128256     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
|  gpt2 |    2 MiB    |   128256   |        N/A       |   128000  |   128009  |    N/A    |    N/A    |      N/A      |       N/A       |      N/A      |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                          |
+-------+--------------+--------------------+-----------------+-----------+----------------+---------------+----------------+----------------+----------------------------------------------+---------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                 VRAM 0                |
|       |              |                    |                 |           |                |               |                |                +--------------------+------------+------------+----------------+---------+------------+
|       |              |                    |                 |           |                |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA   |   NONUMA   |
+-------+--------------+--------------------+-----------------+-----------+----------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+---------+------------+
| llama |    131072    |     2048 / 512     |     Disabled    |  Enabled  |       No       |   Supported   |  127 (126 + 1) |       Yes      |      1 + 0 + 0     | 652.53 MiB | 802.53 MiB |     126 + 1    | 126 GiB | 247.59 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+---------+------------+

Parse From ModelScope

Note

Allow using MS_ENDPOINT to override the default ModelScope endpoint: https://modelscope.cn.

$ gguf-parser --ms-repo="shaowenchen/chinese-alpaca-2-13b-16k-gguf" --ms-file="chinese-alpaca-2-13b-16k.Q5_K.gguf"
+------------------------------------------------------------------------------------------+
| METADATA                                                                                 |
+-------+------+-------+----------------+---------------+----------+------------+----------+
|  TYPE | NAME |  ARCH |  QUANTIZATION  | LITTLE ENDIAN |   SIZE   | PARAMETERS |    BPW   |
+-------+------+-------+----------------+---------------+----------+------------+----------+
| model |  ..  | llama | IQ3_XXS/Q5_K_M |      true     | 8.76 GiB |   13.25 B  | 5.68 bpw |
+-------+------+-------+----------------+---------------+----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      16384      |      5120     |       1       |       true       |         N/A        |   40   |       13824      |      0     |      55296     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| llama |  769.83 KiB |    55296   |        N/A       |     1     |     2     |    N/A    |    N/A    |      N/A      |       N/A       |      N/A      |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                         |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+----------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                 VRAM 0                 |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+-----------+-----------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |    UMA    |   NONUMA  |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+-----------+-----------+
| llama |     16384    |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |   Supported   |   41 (40 + 1)  |       Yes      |      1 + 0 + 0     | 144.95 MiB | 294.95 MiB |     40 + 1     | 12.50 GiB | 22.96 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+-----------+-----------+

Parse From Ollama Library

Note

Allow using --ol-base-url to override the default Ollama registry endpoint: https://registry.ollama.ai.

$ gguf-parser --ol-model="llama3.1"
+-----------------------------------------------------------------------------------------------------------+
| METADATA                                                                                                  |
+-------+-------------------------+-------+--------------+---------------+----------+------------+----------+
|  TYPE |           NAME          |  ARCH | QUANTIZATION | LITTLE ENDIAN |   SIZE   | PARAMETERS |    BPW   |
+-------+-------------------------+-------+--------------+---------------+----------+------------+----------+
| model | Meta Llama 3.1 8B In... | llama |     Q4_0     |      true     | 4.33 GiB |   8.03 B   | 4.64 bpw |
+-------+-------------------------+-------+--------------+---------------+----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      131072     |      4096     |       4       |       true       |         32         |   32   |       14336      |      0     |     128256     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
|  gpt2 |    2 MiB    |   128256   |        N/A       |   128000  |   128009  |    N/A    |    N/A    |      N/A      |       N/A       |      N/A      |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                      |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+-------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                VRAM 0               |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+--------+-----------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |   NONUMA  |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+
| llama |    131072    |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |   Supported   |   33 (32 + 1)  |       Yes      |      1 + 0 + 0     | 403.62 MiB | 553.62 MiB |     32 + 1     | 16 GiB | 29.08 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+

$ # Ollama Model includes the preset params and other artifacts, like multimodal projectors or LoRA adapters, 
$ # you can get the usage of Ollama running by using `--ol-usage` option.

$ gguf-parser --ol-model="llama3.1" --ol-usage
+-----------------------------------------------------------------------------------------------------------+
| METADATA                                                                                                  |
+-------+-------------------------+-------+--------------+---------------+----------+------------+----------+
|  TYPE |           NAME          |  ARCH | QUANTIZATION | LITTLE ENDIAN |   SIZE   | PARAMETERS |    BPW   |
+-------+-------------------------+-------+--------------+---------------+----------+------------+----------+
| model | Meta Llama 3.1 8B In... | llama |     Q4_0     |      true     | 4.33 GiB |   8.03 B   | 4.64 bpw |
+-------+-------------------------+-------+--------------+---------------+----------+------------+----------+

+---------------------------------------------------------------------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                                                                                      |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
| MAX CONTEXT LEN | EMBEDDING LEN | EMBEDDING GQA | ATTENTION CAUSAL | ATTENTION HEAD CNT | LAYERS | FEED FORWARD LEN | EXPERT CNT | VOCABULARY LEN |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+
|      131072     |      4096     |       4       |       true       |         32         |   32   |       14336      |      0     |     128256     |
+-----------------+---------------+---------------+------------------+--------------------+--------+------------------+------------+----------------+

+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| TOKENIZER                                                                                                                                             |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
| MODEL | TOKENS SIZE | TOKENS LEN | ADDED TOKENS LEN | BOS TOKEN | EOS TOKEN | EOT TOKEN | EOM TOKEN | UNKNOWN TOKEN | SEPARATOR TOKEN | PADDING TOKEN |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+
|  gpt2 |    2 MiB    |   128256   |        N/A       |   128000  |   128009  |    N/A    |    N/A    |      N/A      |       N/A       |      N/A      |
+-------+-------------+------------+------------------+-----------+-----------+-----------+-----------+---------------+-----------------+---------------+

+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                         |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+----------------------------------------------+----------------------------------------+
|  ARCH | CONTEXT SIZE | BATCH SIZE (L / P) | FLASH ATTENTION | MMAP LOAD | EMBEDDING ONLY |  RERANKING  | DISTRIBUTABLE | OFFLOAD LAYERS | FULL OFFLOADED |                      RAM                     |                 VRAM 0                 |
|       |              |                    |                 |           |                |             |               |                |                +--------------------+------------+------------+----------------+------------+----------+
|       |              |                    |                 |           |                |             |               |                |                | LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |     UMA    |  NONUMA  |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+------------+----------+
| llama |     2048     |     2048 / 512     |     Disabled    |  Enabled  |       No       | Unsupported |   Supported   |   33 (32 + 1)  |       Yes      |      1 + 0 + 0     | 151.62 MiB | 301.62 MiB |     32 + 1     | 256.50 MiB | 4.81 GiB |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+------------+----------+

Others

Parse Image Model
$ # Parse FLUX.1-dev Model
$ gguf-parser --hf-repo="gpustack/FLUX.1-dev-GGUF" --hf-file="FLUX.1-dev-FP16.gguf"
+----------------------------------------------------------------------------------------------+
| METADATA                                                                                     |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+
|  TYPE | NAME |    ARCH   | QUANTIZATION | LITTLE ENDIAN |    SIZE   | PARAMETERS |    BPW    |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+
| model |  N/A | diffusion |      F16     |      true     | 31.79 GiB |    17 B    | 16.06 bpw |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+

+-------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                        |
+----------------+-------------------------------------------------+------------------+
| DIFFUSION ARCH |                   CONDITIONERS                  |    AUTOENCODER   |
+----------------+-------------------------------------------------+------------------+
|     FLUX.1     | OpenAI CLIP ViT-L/14 (F16), Google T5-xxl (F16) | FLUX.1 VAE (F16) |
+----------------+-------------------------------------------------+------------------+

+--------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                 |
+--------+-----------------+-------------+---------------+----------------+------------------------+-----------------------+
|  ARCH  | FLASH ATTENTION |  MMAP LOAD  | DISTRIBUTABLE | FULL OFFLOADED |           RAM          |         VRAM 0        |
|        |                 |             |               |                +-----------+------------+-----------+-----------+
|        |                 |             |               |                |    UMA    |   NONUMA   |    UMA    |   NONUMA  |
+--------+-----------------+-------------+---------------+----------------+-----------+------------+-----------+-----------+
| flux_1 |     Disabled    | Unsupported |  Unsupported  |       Yes      | 87.45 MiB | 237.45 MiB | 31.79 GiB | 41.06 GiB |
+--------+-----------------+-------------+---------------+----------------+-----------+------------+-----------+-----------+

$ # Parse FLUX.1-dev Model without offload Conditioner and Autoencoder
$ gguf-parser --hf-repo="gpustack/FLUX.1-dev-GGUF" --hf-file="FLUX.1-dev-FP16.gguf" --clip-on-cpu --vae-on-cpu
+----------------------------------------------------------------------------------------------+
| METADATA                                                                                     |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+
|  TYPE | NAME |    ARCH   | QUANTIZATION | LITTLE ENDIAN |    SIZE   | PARAMETERS |    BPW    |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+
| model |  N/A | diffusion |      F16     |      true     | 31.79 GiB |    17 B    | 16.06 bpw |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+

+-------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                        |
+----------------+-------------------------------------------------+------------------+
| DIFFUSION ARCH |                   CONDITIONERS                  |    AUTOENCODER   |
+----------------+-------------------------------------------------+------------------+
|     FLUX.1     | OpenAI CLIP ViT-L/14 (F16), Google T5-xxl (F16) | FLUX.1 VAE (F16) |
+----------------+-------------------------------------------------+------------------+

+-------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                |
+--------+-----------------+-------------+---------------+----------------+-----------------------+-----------------------+
|  ARCH  | FLASH ATTENTION |  MMAP LOAD  | DISTRIBUTABLE | FULL OFFLOADED |          RAM          |         VRAM 0        |
|        |                 |             |               |                +-----------+-----------+-----------+-----------+
|        |                 |             |               |                |    UMA    |   NONUMA  |    UMA    |   NONUMA  |
+--------+-----------------+-------------+---------------+----------------+-----------+-----------+-----------+-----------+
| flux_1 |     Disabled    | Unsupported |  Unsupported  |       Yes      | 16.09 GiB | 16.24 GiB | 22.29 GiB | 25.05 GiB |
+--------+-----------------+-------------+---------------+----------------+-----------+-----------+-----------+-----------+

$ # Parse FLUX.1-dev Model with Autoencoder tiling
$ gguf-parser --hf-repo="gpustack/FLUX.1-dev-GGUF" --hf-file="FLUX.1-dev-FP16.gguf" --vae-tiling
+----------------------------------------------------------------------------------------------+
| METADATA                                                                                     |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+
|  TYPE | NAME |    ARCH   | QUANTIZATION | LITTLE ENDIAN |    SIZE   | PARAMETERS |    BPW    |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+
| model |  N/A | diffusion |      F16     |      true     | 31.79 GiB |    17 B    | 16.06 bpw |
+-------+------+-----------+--------------+---------------+-----------+------------+-----------+

+-------------------------------------------------------------------------------------+
| ARCHITECTURE                                                                        |
+----------------+-------------------------------------------------+------------------+
| DIFFUSION ARCH |                   CONDITIONERS                  |    AUTOENCODER   |
+----------------+-------------------------------------------------+------------------+
|     FLUX.1     | OpenAI CLIP ViT-L/14 (F16), Google T5-xxl (F16) | FLUX.1 VAE (F16) |
+----------------+-------------------------------------------------+------------------+

+--------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                 |
+--------+-----------------+-------------+---------------+----------------+------------------------+-----------------------+
|  ARCH  | FLASH ATTENTION |  MMAP LOAD  | DISTRIBUTABLE | FULL OFFLOADED |           RAM          |         VRAM 0        |
|        |                 |             |               |                +-----------+------------+-----------+-----------+
|        |                 |             |               |                |    UMA    |   NONUMA   |    UMA    |   NONUMA  |
+--------+-----------------+-------------+---------------+----------------+-----------+------------+-----------+-----------+
| flux_1 |     Disabled    | Unsupported |  Unsupported  |       Yes      | 87.45 MiB | 237.45 MiB | 31.79 GiB | 36.18 GiB |
+--------+-----------------+-------------+---------------+----------------+-----------+------------+-----------+-----------+
Parse None Model
$ # Parse Multi-Modal Projector
$ gguf-parser --hf-repo="xtuner/llava-llama-3-8b-v1_1-gguf" --hf-file="llava-llama-3-8b-v1_1-mmproj-f16.gguf"                                                                        
+-----------------------------------------------------------------------------------------------------------------+
| METADATA                                                                                                        |
+-----------+-------------------------+------+--------------+---------------+------------+------------+-----------+
|    TYPE   |           NAME          | ARCH | QUANTIZATION | LITTLE ENDIAN |    SIZE    | PARAMETERS |    BPW    |
+-----------+-------------------------+------+--------------+---------------+------------+------------+-----------+
| projector | openai/clip-vit-larg... | clip |      F16     |      true     | 595.49 MiB |  311.89 M  | 16.02 bpw |
+-----------+-------------------------+------+--------------+---------------+------------+------------+-----------+

+----------------------------------------------------------------------+
| ARCHITECTURE                                                         |
+----------------+---------------+--------+------------------+---------+
| PROJECTOR TYPE | EMBEDDING LEN | LAYERS | FEED FORWARD LEN | ENCODER |
+----------------+---------------+--------+------------------+---------+
|       mlp      |      1024     |   23   |       4096       |  Vision |
+----------------+---------------+--------+------------------+---------+

$ # Parse LoRA Adapter
$ gguf-parser --hf-repo="ngxson/test_gguf_lora_adapter" --hf-file="lora-Llama-3-Instruct-abliteration-LoRA-8B-f16.gguf"
+---------------------------------------------------------------------------------------------+
| METADATA                                                                                    |
+---------+------+-------+--------------+---------------+------------+------------+-----------+
|   TYPE  | NAME |  ARCH | QUANTIZATION | LITTLE ENDIAN |    SIZE    | PARAMETERS |    BPW    |
+---------+------+-------+--------------+---------------+------------+------------+-----------+
| adapter |  N/A | llama |      F16     |      true     | 168.08 MiB |   88.12 M  | 16.00 bpw |
+---------+------+-------+--------------+---------------+------------+------------+-----------+

+---------------------------+
| ARCHITECTURE              |
+--------------+------------+
| ADAPTER TYPE | LORA ALPHA |
+--------------+------------+
|     lora     |     32     |
+--------------+------------+

Estimate

Across Multiple GPU Devices

Imaging you're preparing to run the hierholzer/Llama-3.1-70B-Instruct-GGUF model file across several hosts in your local network. Some of these hosts are equipped with GPU devices, while others do not have any GPU capabilities.

flowchart TD
    subgraph host4["Windows 11 (host4)"]
        ram40(["11GiB RAM remaining"])
    end
    subgraph host3["Apple macOS (host3)"]
        gpu10["Apple M1 Max (6GiB VRAM remaining)"]
    end
    subgraph host2["Windows 11 (host2)"]
        gpu20["NVIDIA 4090 (12GiB VRAM remaining)"]
    end
    subgraph host1["Ubuntu (host1)"]
        gpu30["NVIDIA 4080 0 (8GiB VRAM remaining)"]
        gpu31["NVIDIA 4080 1 (10GiB VRAM remaining)"]
    end
Loading
Single Host Multiple GPU Devices

Let's assume you plan to run the model on host1 only.

flowchart TD
    subgraph host1["Ubuntu (host1)"]
        gpu30["NVIDIA 4080 0 (8GiB VRAM remaining)"]
        gpu31["NVIDIA 4080 1 (10GiB VRAM remaining)"]
    end
Loading
$ gguf-parser --hf-repo="hierholzer/Llama-3.1-70B-Instruct-GGUF" --hf-file="Llama-3.1-70B-Instruct-Q4_K_M.gguf" --skip-metadata --skip-architecture --skip-tokenizer --ctx-size=1024 --tensor-split="8,10" --in-short
+------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                     |
+----------------------------------------------+--------------------------------------+----------------------------------------+
|                      RAM                     |                VRAM 0                |                 VRAM 1                 |
+--------------------+------------+------------+----------------+---------+-----------+----------------+-----------+-----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA   |   NONUMA  | LAYERS (T + O) |    UMA    |   NONUMA  |
+--------------------+------------+------------+----------------+---------+-----------+----------------+-----------+-----------+
|      1 + 0 + 0     | 238.08 MiB | 388.08 MiB |     36 + 0     | 144 MiB | 17.79 GiB |     44 + 1     | 22.01 GiB | 22.51 GiB |
+--------------------+------------+------------+----------------+---------+-----------+----------------+-----------+-----------+

Based on the output provided, serving the hierholzer/Llama-3.1-70B-Instruct-GGUF model on host1 has the following resource consumption:

Host Available RAM Request RAM Available VRAM Request VRAM Result
host1 ENOUGH 388.08 MiB đź‘Ť
host1 (NVIDIA 4080 0) 8 GiB 17.79 GiB
host1 (NVIDIA 4080 1) 10 GiB 22.51 GiB

It appears that running the model on host1 alone is not feasible.

Multiple Hosts Multiple GPU Devices

Next, let's consider the scenario where you plan to run the model on host4, while offloading all layers to host1, host2, and host3.

flowchart TD
    host4 -->|TCP| gpu10
    host4 -->|TCP| gpu20
    host4 -->|TCP| gpu30
    host4 -->|TCP| gpu31

    subgraph host4["Windows 11 (host4)"]
        ram40(["11GiB RAM remaining"])
    end
    subgraph host3["Apple macOS (host3)"]
        gpu10["Apple M1 Max (6GiB VRAM remaining)"]
    end
    subgraph host2["Windows 11 (host2)"]
        gpu20["NVIDIA 4090 (12GiB VRAM remaining)"]
    end
    subgraph host1["Ubuntu (host1)"]
        gpu30["NVIDIA 4080 0 (8GiB VRAM remaining)"]
        gpu31["NVIDIA 4080 1 (10GiB VRAM remaining)"]
    end
Loading
$ gguf-parser --hf-repo="hierholzer/Llama-3.1-70B-Instruct-GGUF" --hf-file="Llama-3.1-70B-Instruct-Q4_K_M.gguf" --skip-metadata --skip-architecture --skip-tokenizer --ctx-size=1024 --tensor-split="8,10,12,6" --rpc="host1:50052,host1:50053,host2:50052,host3:50052" --in-short
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                 |
+----------------------------------------------+----------------------------------------------+----------------------------------------------+----------------------------------------------+----------------------------------------------+
|                      RAM                     |                 RPC 0 (V)RAM                 |                 RPC 1 (V)RAM                 |                 RPC 2 (V)RAM                 |                 RPC 3 (V)RAM                 |
+--------------------+------------+------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |      UMA     |    NONUMA    |
+--------------------+------------+------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+
|      1 + 0 + 0     | 238.08 MiB | 388.08 MiB |     18 + 0     |   8.85 GiB   |   9.28 GiB   |     23 + 0     |   10.88 GiB  |   11.32 GiB  |     27 + 0     |   12.75 GiB  |   13.19 GiB  |     12 + 1     |   6.87 GiB   |   7.38 GiB   |
+--------------------+------------+------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+

According to the output provided, serving the hierholzer/Llama-3.1-70B-Instruct-GGUF model on host4 results in the following resource consumption:

Host Available RAM Request RAM Available VRAM Request VRAM Result
host4 11 GiB 388.08 MiB đź‘Ť
host1 (NVIDIA 4080 0) 8 GiB 9.28 GiB
host1 (NVIDIA 4080 1) 10 GiB 11.32 GiB
host2 (NVIDIA 4090) 12 GiB 13.19 GiB
host3 (Apple M1 Max) ENOUGH 6 GiB 6.87 GiB

It seems that the model cannot be served on host4, even with all layers offloaded to host1, host2, and host3.

We should consider a different approach: running the model on host3 while offloading all layers to host1, host2, and host4.

flowchart TD
    host3 -->|TCP| ram40
    host3 -->|TCP| gpu20
    host3 -->|TCP| gpu30
    host3 -->|TCP| gpu31

    subgraph host4["Windows 11 (host4)"]
        ram40(["11GiB RAM remaining"])
    end
    subgraph host3["Apple macOS (host3)"]
        gpu10["Apple M1 Max (6GiB VRAM remaining)"]
    end
    subgraph host2["Windows 11 (host2)"]
        gpu20["NVIDIA 4090 (12GiB VRAM remaining)"]
    end
    subgraph host1["Ubuntu (host1)"]
        gpu30["NVIDIA 4080 0 (8GiB VRAM remaining)"]
        gpu31["NVIDIA 4080 1 (10GiB VRAM remaining)"]
    end
Loading
$ gguf-parser --hf-repo="hierholzer/Llama-3.1-70B-Instruct-GGUF" --hf-file="Llama-3.1-70B-Instruct-Q4_K_M.gguf" --skip-metadata --skip-architecture --skip-tokenizer --ctx-size=1024 --tensor-split="11,12,8,10,6" --rpc="host4:50052,host2:50052,host1:50052,host1:50053" --in-short
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                                                                                                                         |
+----------------------------------------------+----------------------------------------------+----------------------------------------------+----------------------------------------------+----------------------------------------------+---------------------------------------+
|                      RAM                     |                 RPC 0 (V)RAM                 |                 RPC 1 (V)RAM                 |                 RPC 2 (V)RAM                 |                 RPC 3 (V)RAM                 |                 VRAM 0                |
+--------------------+------------+------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+-----------+----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |    UMA    |  NONUMA  |
+--------------------+------------+------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+-----------+----------+
|      1 + 0 + 0     | 238.08 MiB | 388.08 MiB |     19 + 0     |   9.36 GiB   |   9.79 GiB   |     21 + 0     |   9.92 GiB   |   10.36 GiB  |     14 + 0     |   6.57 GiB   |   7.01 GiB   |     17 + 0     |   8.11 GiB   |   8.54 GiB   |      9 + 1     | 36.52 MiB | 5.91 GiB |
+--------------------+------------+------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+--------------+--------------+----------------+-----------+----------+

According to the output provided, serving the hierholzer/Llama-3.1-70B-Instruct-GGUF model on host3 results in the following resource consumption:

Host Available RAM Request RAM Available VRAM Request VRAM Result
host3 (Apple M1 Max) ENOUGH 238.08 MiB đź‘Ť
host4 11 GiB 9.79 GiB đź‘Ť
host2 (NVIDIA 4090) 12 GiB 10.36 GiB đź‘Ť
host1 (NVIDIA 4080 0) 8 GiB 7.01 GiB đź‘Ť
host1 (NVIDIA 4080 1) 10 GiB 8.54 GiB đź‘Ť
host3 (Apple M1 Max) 6 GiB 36.52 MiB đź‘Ť

Now, the model can be successfully served on host3, with all layers offloaded to host1, host2, and host4.

Maximum Tokens Per Second

The maximum TPS estimation for the GGUF Parser is determined by the model's parameter size, context size, model offloaded layers, and devices on which the model runs. Among these factors, the device's specifications are particularly important.

Inspired by LLM inference speed of light, GGUF Parser use the FLOPS and bandwidth of the device as evaluation metrics:

  • When the device is a CPU, FLOPS refers to the performance of that CPU, while bandwidth corresponds to the DRAM bandwidth.
  • When the device is a (i)GPU, FLOPS indicates the performance of that (i)GPU, and bandwidth corresponds to the VRAM bandwidth.
  • When the device is a specific host, FLOPS depends on whether the CPU or (i)GPU of that host is being used, while bandwidth corresponds to the bandwidth connecting the main node to that host. After all, a chain is only as strong as its weakest link. If the connection bandwidth between the main node and the host is equal to or greater than the *RAM bandwidth, then the bandwidth should be taken as the *RAM bandwidth value.
CPU FLOPS Calculation

The performance of a single CPU cache can be calculated using the following formula:

$$ CPU\ FLOPS = Number\ of \ Cores \times Core\ Frequency \times Floating\ Point\ Operations\ per\ Cycle $$

The Apple M1 Max CPU features a total of 10 cores, consisting of 8 performance cores and 2 efficiency cores. The performance cores operate at a clock speed of 3.2 GHz, while the efficiency cores run at 2.2 GHz. All cores support the ARM NEON instruction set, which enables 128-bit SIMD operations, allowing multiple floating-point numbers to be processed simultaneously within a single CPU cycle. Specifically, using single-precision (32-bit) floating-point numbers, each cycle can handle 4 floating-point operations.

The peak floating-point performance for a single performance core is calculated as follows:

$$ Peak\ Performance = 3.2\ GHz \times 4\ FLOPS = 12.8\ GFLOPS $$

For a single efficiency core, the calculation is:

$$ Peak\ Performance = 2.2\ GHz \times 4\ FLOPS = 8.8\ GFLOPS $$

Thus, the overall peak floating-point performance of the entire CPU can be determined by combining the contributions from both types of cores:

$$ Peak\ Performance = 8\ Cores \times 12.8\ GFLOPS + 2\ Cores \times 8.8\ GFLOPS = 120\ GFLOPS $$

This results in an average performance of 12 GFLOPS per core. It is evident that the average performance achieved by utilizing both performance and efficiency cores is lower than that obtained by exclusively using performance cores.

Run LLaMA2-7B-Chat with Apple Silicon M-series

Taking TheBloke/Llama-2-7B-Chat-GGUF as an example and estimate the maximum tokens per second for Apple Silicon M-series using the GGUF Parser.

$ # Estimate full offloaded Q8_0 model
$ gguf-parser --hf-repo TheBloke/LLaMA-7b-GGUF --hf-file llama-7b.Q8_0.gguf --skip-metadata --skip-architecture --skip-tokenizer --in-short \
  -c 512 \
  --device-metric "<CPU FLOPS>;<RAM BW>,<iGPU FLOPS>;<VRAM BW>"

$ # Estimate full offloaded Q4_0 model
$ gguf-parser --hf-repo TheBloke/LLaMA-7b-GGUF --hf-file llama-7b.Q4_0.gguf --skip-metadata --skip-architecture --skip-tokenizer --in-short \
  -c 512 \
  --device-metric "<CPU FLOPS>;<RAM BW>,<iGPU FLOPS>;<VRAM BW>"
Variant CPU FLOPS (Performance Core) iGPU FLOPS (V)RAM Bandwidth Q8_0 Max TPS Q4_0 Max TPS
M1 51.2 GFLOPS (4 cores) 2.6 TFLOPS (8 cores) 68.3 GBps 8.68 14.56
M1 Pro 102.4 GFLOPS (8 cores) 5.2 TFLOPS (16 cores) 204.8 GBps 26.04 43.66
M1 Max 102.4 GFLOPS (8 cores) 10.4 TFLOPS (32 cores) 409.6 GBps 52.08 87.31
M1 Ultra 204.8 GFLOPS (16 cores) 21 TFLOPS (64 cores) 819.2 GBps 104.16 174.62
M2 56 GFLOPS (4 cores) 3.6 TFLOPS (10 cores) 102.4 GBps 13.02 21.83
M2 Pro 112 GFLOPS (8 cores) 6.8 TFLOPS (19 cores) 204.8 GBps 26.04 43.66
M2 Max 112 GFLOPS (8 cores) 13.6 TFLOPS (38 cores) 409.6 GBps 52.08 87.31
M2 Ultra 224 GFLOPS (16 cores) 27.2 TFLOPS (76 cores) 819.2 GBps 104.16 174.62
M3 64.96 GFLOPS (4 cores) 4.1 TFLOPS (10 cores) 102.4 GBps 13.02 21.83
M3 Pro 97.44 GFLOPS (6 cores) 7.4 TFLOPS (18 cores) 153.6 GBps 19.53 32.74
M3 Max 194.88 GFLOPS (12 cores) 16.4 TFLOPS (40 cores) 409.6 GBps 52.08 87.31
M4 70.56 GFLOPS (4 cores) 4.1 TFLOPS 120 GBps 15.26 25.58

References:

You can further verify the above results in Performance of llama.cpp on Apple Silicon M-series .

Run LLaMA3.1-405B-Instruct with Apple Mac Studio devices combined with Thunderbolt

Example by leafspark/Meta-Llama-3.1-405B-Instruct-GGUF and estimate the maximum tokens per second for three Apple Mac Studio devices combined with Thunderbolt.

Device CPU FLOPS (Performance Core) iGPU FLOPS (V)RAM Bandwidth Thunderbolt Bandwidth Role
Apple Mac Studio (M2 Ultra) 0 224 GFLOPS (16 cores) 27.2 TFLOPS (76 cores) 819.2 GBps 40 Gbps Main
Apple Mac Studio (M2 Ultra) 1 224 GFLOPS (16 cores) 27.2 TFLOPS (76 cores) 819.2 GBps 40 Gbps RPC Server
Apple Mac Studio (M2 Ultra) 2 224 GFLOPS (16 cores) 27.2 TFLOPS (76 cores) 819.2 GBps 40 Gbps RPC Server

Get the maximum tokens per second with the following command:

$ # Explain the command:
$ # --device-metric "224GFLOPS;819.2GBps"         <-- Apple Mac Studio 0 CPU FLOPS and RAM Bandwidth
$ # --device-metric "27.2TFLOPS;819.2GBps;40Gbps" <-- Apple Mac Studio 1 (RPC 0) iGPU FLOPS, VRAM Bandwidth, and Thunderbolt Bandwidth
$ # --device-metric "27.2TFLOPS;819.2GBps;40Gbps" <-- Apple Mac Studio 2 (RPC 1) iGPU FLOPS, VRAM Bandwidth, and Thunderbolt Bandwidth
$ # --device-metric "27.2TFLOPS;819.2GBps"        <-- Apple Mac Studio 0 iGPU FLOPS and VRAM Bandwidth
$ gguf-parser --hf-repo leafspark/Meta-Llama-3.1-405B-Instruct-GGUF --hf-file Llama-3.1-405B-Instruct.Q4_0.gguf/Llama-3.1-405B-Instruct.Q4_0-00001-of-00012.gguf --skip-metadata --skip-architecture --skip-tokenizer --in-short \
  --no-mmap \
  -c 512 \
  --rpc host1:port,host2:port \
  --tensor-split "<Proportions>" \
  --device-metric "224GFLOPS;819.2GBps" \
  --device-metric "27.2TFLOPS;819.2GBps;40Gbps" \
  --device-metric "27.2TFLOPS;819.2GBps;40Gbps" \
  --device-metric "27.2TFLOPS;819.2GBps"
Tensor Split Apple Mac Studio 0 RAM Apple Mac Studio 1 VRAM (RPC 0) Apple Mac Studio 2 VRAM (RPC 1) Apple Mac Studio 0 VRAM Q4_0 Max TPS
1,1,1 1.99 GiB 72.74 GiB 71.04 GiB 70.96 GiB 10.71
2,1,1 1.99 GiB 108.26 GiB 54.13 GiB 52.35 GiB 11.96
3,1,1 1.99 GiB 130.25 GiB 42.29 GiB 42.20 GiB 9.10
4,1,1 1.99 GiB 143.78 GiB 35.52 GiB 35.44 GiB 7.60
Run Qwen2.5-72B-Instruct with NVIDIA RTX 4080 and remote RPC by Apple Mac Studio (M2)

Example by Qwen/Qwen2.5-72B-Instruct-GGUF and estimate the maximum tokens per second for NVIDIA RTX 4080.

Hardware FLOPS Bandwidth
Intel i5-14600k 510.4 GFLOPS
2 x Corsair Vengeance RGB DDR5-6000 (32GiB) 96 GBps
2 x NVIDIA GeForce RTX 4080 48.74 TFLOPS 736.3 GBps
Apple Mac Studio (M2) 27.2 TFLOPS 819.2 GBps
$ # Explain the command:
$ # --tensor-split 20369,12935,13325               <-- Available Memory in MiB for each device
$ # --device-metric "510.4GFLOPS;96GBps"           <-- Intel i5-14600k CPU FLOPS and RAM Bandwidth
$ # --device-metric "27.2TFLOPS;819.2GBps;40Gbps"  <-- Apple Mac Studio (M2) (RPC 0) iGPU FLOPS, VRAM Bandwidth, and Thunderbolt Bandwidth
$ # --device-metric "48.74TFLOPS;736.3GBps;64GBps" <-- NVIDIA GeForce RTX 0 4080 GPU FLOPS, VRAM Bandwidth, and PCIe 5.0 x16 Bandwidth
$ # --device-metric "48.74TFLOPS;736.3GBps;8GBps"  <-- NVIDIA GeForce RTX 1 4080 GPU FLOPS, VRAM Bandwidth, and PCIe 4.0 x4 Bandwidth
$ gguf-parser --hf-repo Qwen/Qwen2.5-72B-Instruct-GGUF --hf-file qwen2.5-72b-instruct-q4_k_m-00001-of-00012.gguf --skip-metadata --skip-architecture --skip-tokenizer --in-short \
  --no-mmap \
  -c 8192 \
  --rpc host:port \
  --tensor-split 20369,12935,13325 \
  --device-metric "510.4GFLOPS;96GBps" \
  --device-metric "27.2TFLOPS;819.2GBps;40Gbps" \
  --device-metric "48.74TFLOPS;736.3GBps;64GBps" \
  --device-metric "48.74TFLOPS;736.3GBps;8GBps"
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ESTIMATE                                                                                                                                                                           |
+-----------+------------------------------------------+----------------------------------------------+----------------------------------------+-------------------------------------+
|  MAX TPS  |                    RAM                   |                 RPC 0 (V)RAM                 |                 VRAM 0                 |                VRAM 1               |
|           +--------------------+----------+----------+----------------+--------------+--------------+----------------+-----------+-----------+----------------+-----------+--------+
|           | LAYERS (I + T + O) |    UMA   |  NONUMA  | LAYERS (T + O) |      UMA     |    NONUMA    | LAYERS (T + O) |    UMA    |   NONUMA  | LAYERS (T + O) |    UMA    | NONUMA |
+-----------+--------------------+----------+----------+----------------+--------------+--------------+----------------+-----------+-----------+----------------+-----------+--------+
| 51.82 tps |      1 + 0 + 0     | 1.19 GiB | 1.34 GiB |     36 + 0     |   18.85 GiB  |   20.20 GiB  |     22 + 0     | 11.34 GiB | 12.69 GiB |     22 + 1     | 12.65 GiB | 14 GiB |
+-----------+--------------------+----------+----------+----------------+--------------+--------------+----------------+-----------+-----------+----------------+-----------+--------+

Full Layers Offload (default)

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --in-short
+--------------------------------------------------------------------------------------+
| ESTIMATE                                                                             |
+----------------------------------------------+---------------------------------------+
|                      RAM                     |                 VRAM 0                |
+--------------------+------------+------------+----------------+---------+------------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA   |   NONUMA   |
+--------------------+------------+------------+----------------+---------+------------+
|      1 + 0 + 0     | 652.53 MiB | 802.53 MiB |     126 + 1    | 126 GiB | 247.59 GiB |
+--------------------+------------+------------+----------------+---------+------------+

Zero Layers Offload

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --gpu-layers=0 --in-short
+------------------------------------------------------------------------------------+
| ESTIMATE                                                                           |
+----------------------------------------------+-------------------------------------+
|                      RAM                     |                VRAM 0               |
+--------------------+------------+------------+----------------+--------+-----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |   NONUMA  |
+--------------------+------------+------------+----------------+--------+-----------+
|     1 + 126 + 1    | 126.37 GiB | 126.52 GiB |      0 + 0     |   0 B  | 33.34 GiB |
+--------------------+------------+------------+----------------+--------+-----------+

Specific Layers Offload

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --gpu-layers=10 --in-short
+------------------------------------------------------------------------------------+
| ESTIMATE                                                                           |
+----------------------------------------------+-------------------------------------+
|                      RAM                     |                VRAM 0               |
+--------------------+------------+------------+----------------+--------+-----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |   NONUMA  |
+--------------------+------------+------------+----------------+--------+-----------+
|     1 + 116 + 1    | 116.64 GiB | 116.78 GiB |     10 + 0     | 10 GiB | 50.39 GiB |
+--------------------+------------+------------+----------------+--------+-----------+

Specific Context Size

By default, the context size retrieved from the model's metadata.

Use --ctx-size to specify the context size.

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --ctx-size=4096 --in-short
+--------------------------------------------------------------------------------------+
| ESTIMATE                                                                             |
+----------------------------------------------+---------------------------------------+
|                      RAM                     |                 VRAM 0                |
+--------------------+------------+------------+----------------+----------+-----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |    UMA   |   NONUMA  |
+--------------------+------------+------------+----------------+----------+-----------+
|      1 + 0 + 0     | 404.53 MiB | 554.53 MiB |     126 + 1    | 3.94 GiB | 93.31 GiB |
+--------------------+------------+------------+----------------+----------+-----------+

Enable Flash Attention

By default, LLaMA.cpp disables the Flash Attention.

Enable Flash Attention will reduce the VRAM usage, but it also increases the GPU/CPU usage.

Use --flash-attention to enable the Flash Attention.

Please note that not all models support Flash Attention, if the model does not support, the "FLASH ATTENTION" shows " Disabled" even if you enable it.

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --flash-attention --in-short
+--------------------------------------------------------------------------------------+
| ESTIMATE                                                                             |
+----------------------------------------------+---------------------------------------+
|                      RAM                     |                 VRAM 0                |
+--------------------+------------+------------+----------------+---------+------------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA   |   NONUMA   |
+--------------------+------------+------------+----------------+---------+------------+
|      1 + 0 + 0     | 620.53 MiB | 770.53 MiB |     126 + 1    | 126 GiB | 215.70 GiB |
+--------------------+------------+------------+----------------+---------+------------+

Disable MMap

By default, LLaMA.cpp loads the model via Memory-Mapped.

For Apple MacOS, Memory-Mapped is an efficient way to load the model, and results in a lower VRAM usage. For other platforms, Memory-Mapped affects the first-time model loading speed only.

Use --no-mmap to disable loading the model via Memory-Mapped.

Please note that some models require loading the whole weight into memory, if the model does not support MMap, the "MMAP LOAD" shows "Not Supported".

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --no-mmap --in-short
+-------------------------------------------------------------------------------------+
| ESTIMATE                                                                            |
+------------------------------------------+------------------------------------------+
|                    RAM                   |                  VRAM 0                  |
+--------------------+----------+----------+----------------+------------+------------+
| LAYERS (I + T + O) |    UMA   |  NONUMA  | LAYERS (T + O) |     UMA    |   NONUMA   |
+--------------------+----------+----------+----------------+------------+------------+
|      1 + 0 + 0     | 1.98 GiB | 2.13 GiB |     126 + 1    | 213.97 GiB | 247.59 GiB |
+--------------------+----------+----------+----------------+------------+------------+

With Adapter

Use --lora/--control-vector to estimate the usage when loading a model with adapters.

$ gguf-parser --hf-repo="QuantFactory/Meta-Llama-3-8B-Instruct-GGUF" --hf-file="Meta-Llama-3-8B-Instruct.Q5_K_M.gguf" --skip-metadata --skip-architecture --skip-tokenizer --in-short
+-----------------------------------------------------------------------------------+
| ESTIMATE                                                                          |
+----------------------------------------------+------------------------------------+
|                      RAM                     |               VRAM 0               |
+--------------------+------------+------------+----------------+--------+----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |  NONUMA  |
+--------------------+------------+------------+----------------+--------+----------+
|      1 + 0 + 0     | 163.62 MiB | 313.62 MiB |     32 + 1     |  1 GiB | 6.82 GiB |
+--------------------+------------+------------+----------------+--------+----------+

$ # With a LoRA adapter.
$ gguf-parser --hf-repo="QuantFactory/Meta-Llama-3-8B-Instruct-GGUF" --hf-file="Meta-Llama-3-8B-Instruct.Q5_K_M.gguf" --lora-url="https://huggingface.co/ngxson/test_gguf_lora_adapter/resolve/main/lora-Llama-3-Instruct-abliteration-LoRA-8B-f16.gguf" --skip-metadata --skip-architecture --skip-tokenizer --in-short
+-----------------------------------------------------------------------------------+
| ESTIMATE                                                                          |
+----------------------------------------------+------------------------------------+
|                      RAM                     |               VRAM 0               |
+--------------------+------------+------------+----------------+--------+----------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA  |  NONUMA  |
+--------------------+------------+------------+----------------+--------+----------+
|      1 + 0 + 0     | 176.30 MiB | 326.30 MiB |     32 + 1     |  1 GiB | 6.98 GiB |
+--------------------+------------+------------+----------------+--------+----------+

Get Proper Offload Layers

Use --gpu-layers-step to get the proper offload layers number when the model is too large to fit into the GPUs memory.

$ gguf-parser --hf-repo="etemiz/Llama-3.1-405B-Inst-GGUF" --hf-file="llama-3.1-405b-IQ1_M-00019-of-00019.gguf" --skip-metadata --skip-architecture --skip-tokenizer --gpu-layers-step=6 --in-short
+--------------------------------------------------------------------------------------+
| ESTIMATE                                                                             |
+----------------------------------------------+---------------------------------------+
|                      RAM                     |                 VRAM 0                |
+--------------------+------------+------------+----------------+---------+------------+
| LAYERS (I + T + O) |     UMA    |   NONUMA   | LAYERS (T + O) |   UMA   |   NONUMA   |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 126 + 1    | 126.37 GiB | 126.52 GiB |      0 + 0     |   0 B   |  33.34 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 120 + 1    | 120.64 GiB | 120.78 GiB |      6 + 0     |  6 GiB  |  43.68 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 114 + 1    | 114.64 GiB | 114.78 GiB |     12 + 0     |  12 GiB |  53.74 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 108 + 1    | 108.64 GiB | 108.78 GiB |     18 + 0     |  18 GiB |  63.80 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 102 + 1    | 102.64 GiB | 102.78 GiB |     24 + 0     |  24 GiB |  73.86 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 96 + 1     |  96.64 GiB |  96.78 GiB |     30 + 0     |  30 GiB |  83.93 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 90 + 1     |  90.64 GiB |  90.78 GiB |     36 + 0     |  36 GiB |  93.99 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 84 + 1     |  84.64 GiB |  84.78 GiB |     42 + 0     |  42 GiB | 104.05 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 78 + 1     |  78.64 GiB |  78.78 GiB |     48 + 0     |  48 GiB | 114.11 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 72 + 1     |  72.64 GiB |  72.78 GiB |     54 + 0     |  54 GiB | 124.17 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 66 + 1     |  66.64 GiB |  66.78 GiB |     60 + 0     |  60 GiB | 134.23 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 60 + 1     |  60.64 GiB |  60.78 GiB |     66 + 0     |  66 GiB | 144.29 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 54 + 1     |  54.64 GiB |  54.78 GiB |     72 + 0     |  72 GiB | 154.35 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 48 + 1     |  48.64 GiB |  48.78 GiB |     78 + 0     |  78 GiB | 164.42 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 42 + 1     |  42.64 GiB |  42.78 GiB |     84 + 0     |  84 GiB | 174.48 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 36 + 1     |  36.64 GiB |  36.78 GiB |     90 + 0     |  90 GiB | 184.54 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 30 + 1     |  30.64 GiB |  30.78 GiB |     96 + 0     |  96 GiB | 194.60 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 24 + 1     |  24.64 GiB |  24.78 GiB |     102 + 0    | 102 GiB | 204.66 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 18 + 1     |  18.64 GiB |  18.78 GiB |     108 + 0    | 108 GiB | 214.72 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|     1 + 12 + 1     |  12.64 GiB |  12.78 GiB |     114 + 0    | 114 GiB | 225.05 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|      1 + 6 + 1     |  6.64 GiB  |  6.78 GiB  |     120 + 0    | 120 GiB | 235.64 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|      1 + 0 + 1     | 653.08 MiB | 803.08 MiB |     126 + 0    | 126 GiB | 246.24 GiB |
+--------------------+------------+------------+----------------+---------+------------+
|      1 + 0 + 0     | 652.53 MiB | 802.53 MiB |     126 + 1    | 126 GiB | 247.59 GiB |
+--------------------+------------+------------+----------------+---------+------------+

License

MIT