tl;dr, Review/Check GGUF files and estimate the memory usage.
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.
- 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.
- 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-metricoptions. - GGUF Parser distinguishes the remote devices from
--tensor-splitvia--rpc.- For one host multiple GPU devices, you can use
--tensor-splitto get the estimated memory usage of each GPU. - For multiple hosts multiple GPU devices, you can use
--tensor-splitand--rpcto get the estimated memory usage of each GPU. Since v0.11.0,--rpcflag masks the devices specified by--tensor-splitin front.
- For one host multiple GPU devices, you can use
- Table result usage:
DISTRIBUTABLEindicates the GGUF file supports distribution inference or not, if the file doesn't support distribution inference, you can not offload it with RPC servers.RAMindicates the system memory usage.VRAM *indicates the local GPU memory usage.RPC * (V)RAMindicates the remote memory usage. The kind of memory is determined by which backend the RPC server uses, check the running logs for more details.UMAindicates the memory usage of Apple macOS only.NONUMAadapts 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.
Install from releases.
$ 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 |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+--------+-----------+
$ 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 |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+---------+------------+
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 |
+-------+--------------+--------------------+-----------------+-----------+----------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+---------+------------+
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 |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+-----------+-----------+
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 |
+-------+--------------+--------------------+-----------------+-----------+----------------+-------------+---------------+----------------+----------------+--------------------+------------+------------+----------------+------------+----------+
$ # 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 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 |
+--------------+------------+
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
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
$ 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 | 👍 | ||
| 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.
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
$ 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 | 👍 | ||
| 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
$ 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 | 👍 | ||
| host4 | 11 GiB | 9.79 GiB | 👍 | ||
| host2 (NVIDIA 4090) | 12 GiB | 10.36 GiB | 👍 | ||
| host1 (NVIDIA 4080 0) | 8 GiB | 7.01 GiB | 👍 | ||
| host1 (NVIDIA 4080 1) | 10 GiB | 8.54 GiB | 👍 | ||
| host3 (Apple M1 Max) | 6 GiB | 36.52 MiB | 👍 |
Now, the model can be successfully served on host3, with all layers offloaded to host1, host2, and host4.
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.
The performance of a single CPU cache can be calculated using the following formula:
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:
For a single efficiency core, the calculation is:
Thus, the overall peak floating-point performance of the entire CPU can be determined by combining the contributions from both types of cores:
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.
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 .
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 |
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 |
+-----------+--------------------+----------+----------+----------------+--------------+--------------+----------------+-----------+-----------+----------------+-----------+--------+$ 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 |
+--------------------+------------+------------+----------------+---------+------------+
$ 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 |
+--------------------+------------+------------+----------------+--------+-----------+
$ 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 |
+--------------------+------------+------------+----------------+--------+-----------+
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 |
+--------------------+------------+------------+----------------+----------+-----------+
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 |
+--------------------+------------+------------+----------------+---------+------------+
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 |
+--------------------+----------+----------+----------------+------------+------------+
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 |
+--------------------+------------+------------+----------------+--------+----------+
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 |
+--------------------+------------+------------+----------------+---------+------------+
MIT