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aider/website/_data/quant.yml

@@ -158,4 +158,27 @@
   date: 2024-11-23
   versions: 0.64.2.dev
   seconds_per_case: 35.7
+  total_cost: 0.0000
+
+- dirname: 2024-11-24-02-23-32--deepinfra-qwen-diff
+  test_cases: 133
+  model: Deepinfra (BF16)
+  edit_format: diff
+  commit_hash: bb78e2f
+  pass_rate_1: 58.6
+  pass_rate_2: 72.2
+  percent_cases_well_formed: 94.7
+  error_outputs: 15
+  num_malformed_responses: 13
+  num_with_malformed_responses: 7
+  user_asks: 3
+  lazy_comments: 0
+  syntax_errors: 0
+  indentation_errors: 0
+  exhausted_context_windows: 2
+  test_timeouts: 3
+  command: aider --model deepinfra/Qwen/Qwen2.5-Coder-32B-Instruct
+  date: 2024-11-24
+  versions: 0.64.2.dev
+  seconds_per_case: 17.5
   total_cost: 0.0000

aider/website/_posts/2024-11-21-quantization.md

@@ -32,6 +32,7 @@ served both locally and from cloud providers.
 - [4bit and 8bit quants for mlx](https://t.co/cwX3DYX35D).
 - 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 different quantizations from the [Ollama model library](https://ollama.com/library/qwen2.5-coder:32b-instruct-q4_K_M).
+- Other API providers.
 
 The best version of the model rivals GPT-4o, while the worst performer
 is more like GPT-4 level.