Mistral AIMistral Large 3VSMistral AIMistral Small 4
Our Take
We recommend Mistral Small 4 for practical local execution on standard developer hardware, or Mistral Large 3 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While Mistral Large 3 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose Mistral Small 4 for standard local setups, or Mistral Large 3 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: Mistral Large 3 is a massive 675B parameter model requiring heavy GPU infrastructure, while Mistral Small 4 is a 119B parameter model.
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Benchmarks & Scores
Coding (live-code-bench)
34.4%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)Winner (+14.3%)
85.5%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$0.75Input: $0.50 | Output: $1.50Context Window
262.14k tokensBenchmarks & Scores
Coding (live-code-bench)Winner (+29.2%)
63.6%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)
71.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.9x cheaper
$0.26Input: $0.15 | Output: $0.60Context Window
262.14k tokensFrequently Asked Questions about Mistral Large 3 vs Mistral Small 4
Mistral Small 4 is cheaper than Mistral Large 3. Mistral Small 4 has a blended cost of $0.26/1M tokens, which is about 2.9x cheaper than Mistral Large 3 at $0.75/1M tokens.
Mistral Small 4 is better for coding tasks on this benchmark. It scores 63.6% on live-code-bench (scripting single-file apps or clearly defined functions) compared to Mistral Large 3 which scores 34.4%.
Related Matchups
Explore similar comparisons for Mistral Large 3 and Mistral Small 4.
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