Mistral AI Mistral Small 4 VS OpenAI GPT-5.6 Luna
Decision Recommendation
⚖️ Editorial Verdict: In our analysis, GPT-5.6 Luna is the premium intelligence choice, scoring 62.7% higher on coding benchmarks. However, this accuracy premium comes with a cost overhead: Mistral Small 4 is 1.0x cheaper to run. If you are building high-volume, simple chatbots or processing massive amounts of text where budget is critical, Mistral Small 4 offers excellent cost savings. For agentic reasoning, code refactoring, or complex logical tasks, the accuracy premium of GPT-5.6 Luna fully justifies the cost.
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Model Specs
Mistral Small 4
Benchmarks & Scores
Coding (swe-bench-pro)
N/Aexcellent at multi-file repositories, autonomous agents, and industrial codebases
Reasoning (gpqa-diamond)
N/Agraduate-level science QA
Cost & Performance
Cost (per 1M tokens)
N/AInput: N/A | Output: N/AContext Window
262.14k tokensModel Specs
GPT-5.6 Luna
Benchmarks & Scores
Coding (swe-bench-pro)
62.7%excellent at multi-file repositories, autonomous agents, and industrial codebases
Reasoning (gpqa-diamond)
92.3%graduate-level science QA
Cost & Performance
Cost (per 1M tokens)
$2.25Input: $1.00 | Output: $6.00Context WindowLarger
1.05M tokensFrequently Asked Questions about Mistral Small 4 vs GPT-5.6 Luna comparison
GPT-5.6 Luna is better for coding tasks on this benchmark. It scores 62.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Mistral Small 4 which scores N/A.
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