GoogleGemma 4 12BVSMistral AIMistral Small 4
Our Take
We recommend Gemma 4 12B for practical local execution on standard developer hardware, or Mistral Small 4 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While Mistral Small 4 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose Gemma 4 12B for standard local setups, or Mistral Small 4 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: Mistral Small 4 is a massive 119B parameter model requiring heavy GPU infrastructure, while Gemma 4 12B is a 11.95B parameter model.
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Benchmarks & Scores
Coding (live-code-bench)Winner (+8.4%)
72%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)Winner (+7.6%)
78.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
262.14k tokensBenchmarks & Scores
Coding (live-code-bench)
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)
$0.26Input: $0.15 | Output: $0.60Context Window
262.14k tokensFrequently Asked Questions about Gemma 4 12B vs Mistral Small 4
Gemma 4 12B is better for coding tasks on this benchmark. It scores 72% on live-code-bench (scripting single-file apps or clearly defined functions) compared to Mistral Small 4 which scores 63.6%.
Related Matchups
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