diff --git a/aider/website/_posts/2024-11-21-quantization.md b/aider/website/_posts/2024-11-21-quantization.md
index 6b65658cf4e..617c3fb9cd7 100644
--- a/aider/website/_posts/2024-11-21-quantization.md
+++ b/aider/website/_posts/2024-11-21-quantization.md
@@ -10,6 +10,7 @@ nav_exclude: true
{% endif %}
# Quantization matters
+{: .no_toc }
Open source models like Qwen 2.5 32B Instruct are performing very well on
aider's code editing benchmark, rivaling closed source frontier models.
@@ -18,8 +19,7 @@ can impact code editing skill.
Heavily quantized models are often used by cloud API providers
and local model servers like Ollama or MLX.
-
-The graph above compares different versions of the Qwen 2.5 Coder 32B Instruct model,
+The graph and table below 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).
@@ -38,9 +38,17 @@ It's unclear why this is happening to just this provider.
The other providers available through OpenRouter perform similarly
when their API is accessed directly.
+### Sections
+{: .no_toc }
+
+- TOC
+{:toc}
+
{: .note }
This article is being updated as additional benchmark runs complete.
+## Benchmark results
+