diff --git a/aider/website/_data/quant.yml b/aider/website/_data/quant.yml
index c84755dca3..baaefa6585 100644
--- a/aider/website/_data/quant.yml
+++ b/aider/website/_data/quant.yml
@@ -22,6 +22,29 @@
seconds_per_case: 22.5
total_cost: 0.0000
+- dirname: 2024-11-22-18-56-13--ollama-qwen2.5-coder:32b-instruct-fp16
+ test_cases: 132
+ model: ollama/qwen2.5-coder:32b-instruct-fp16 (64k context)
+ edit_format: diff
+ commit_hash: f06452c-dirty, 6a0a97c-dirty, 4e9ae16-dirty, 5506d0f-dirty
+ pass_rate_1: 58.3
+ pass_rate_2: 71.4
+ percent_cases_well_formed: 90.2
+ error_outputs: 27
+ num_malformed_responses: 26
+ num_with_malformed_responses: 13
+ user_asks: 2
+ lazy_comments: 0
+ syntax_errors: 0
+ indentation_errors: 0
+ exhausted_context_windows: 0
+ test_timeouts: 0
+ command: aider --model ollama/qwen2.5-coder:32b-instruct-fp16
+ date: 2024-11-22
+ versions: 0.64.2.dev
+ seconds_per_case: 119.6
+ total_cost: 0.0000
+
- dirname: 2024-11-22-14-53-26--hyperbolic-qwen25coder32binstruct
test_cases: 133
model: Hyperbolic BF16
diff --git a/aider/website/_posts/2024-11-21-quantization.md b/aider/website/_posts/2024-11-21-quantization.md
index 3e4ba910c2..2d8391ac56 100644
--- a/aider/website/_posts/2024-11-21-quantization.md
+++ b/aider/website/_posts/2024-11-21-quantization.md
@@ -18,17 +18,20 @@ can strongly impact code editing skill.
Heavily quantized models are often used by cloud API providers
and local model servers like Ollama.
-
+
-The graph above compares 4 different versions of the Qwen 2.5 Coder 32B Instruct model,
+The graph above compares different versions of the Qwen 2.5 Coder 32B Instruct model,
served both locally and from cloud providers.
- The [HuggingFace BF16 weights](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct) served via [glhf.chat](https://glhf.chat).
- Hyperbolic labs API for [qwen2-5-coder-32b-instruct](https://app.hyperbolic.xyz/models/qwen2-5-coder-32b-instruct), which is using BF16. This result is probably within the expected variance of the HF result.
+- A [4bit quant for mlx](https://t.co/cwX3DYX35D).
+This is the only model which was benchmarked using the "whole" [edit format](https://aider.chat/docs/more/edit-formats.html).
+The rest were benchmarked with the much more practical and challenging "diff"edit format.
- The results from [OpenRouter's mix of providers](https://openrouter.ai/qwen/qwen-2.5-coder-32b-instruct/providers) which serve the model with different levels of quantization.
- Ollama locally serving [qwen2.5-coder:32b-instruct-q4_K_M)](https://ollama.com/library/qwen2.5-coder:32b-instruct-q4_K_M), which has `Q4_K_M` quantization, with Ollama's default 2k context window.