Mistral AI Mistral Medium 3.5 VS OpenAI GPT-5.6 Luna
Decision Recommendation
👑 Editorial Verdict: GPT-5.6 Luna strictly dominates Mistral Medium 3.5 across all compared dimensions. It is not only more cost-effective (blended cost of $2.25 vs $3.00 per 1M tokens) but also delivers superior coding accuracy (62.7% vs 0% on SWE-bench). Unless you have platform lock-in, GPT-5.6 Luna is the clear and optimal choice for all development workloads.
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Model Specs
Mistral Medium 3.5
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)
$3.00Input: $1.50 | Output: $7.50Context 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)1.3x cheaper
$2.25Input: $1.00 | Output: $6.00Context WindowLarger
1.05M tokensFrequently Asked Questions about Mistral Medium 3.5 vs GPT-5.6 Luna comparison
GPT-5.6 Luna is cheaper than Mistral Medium 3.5. GPT-5.6 Luna has a blended cost of $2.25/1M tokens, which is about 1.3x cheaper than Mistral Medium 3.5 at $3.00/1M tokens.
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 Medium 3.5 which scores N/A.
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