Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.1 Codex mini (high) | Mistral Medium 3.1 |
|---|---|---|
| Input ($/M tokens) | $0.25 | $0.4 |
| Output ($/M tokens) | $2 | $2 |
Verdict. GPT-5.1 Codex mini (high) and Mistral Medium 3.1 split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Mistral Medium 3.1 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Medium 3.1 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.1 Codex mini (high) is strongest on Intelligence Index (31.3). Mistral Medium 3.1 leads on Coding Index (20.5), Intelligence Index (14.7).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. OpenAI and Mistral sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Mistral often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GPT-5.1 Codex mini (high) costs $37.50 ($450/year); Mistral Medium 3.1 costs $42.00 ($504/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.1 Codex mini (high) ≈ $5.25/run, Mistral Medium 3.1 ≈ $6.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.1 Codex mini (high) ≈ $250/run, Mistral Medium 3.1 ≈ $280/run. GPT-5.1 Codex mini (high) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
GPT-5.1 Codex mini (high) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.69/M tokens vs $0.80/M for Mistral Medium 3.1.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
Mistral Medium 3.1 generates tokens faster at 106 tok/s vs — tok/s. However, Mistral Medium 3.1 has lower time-to-first-token (1.47s vs —s).
Choose based on your priorities: GPT-5.1 Codex mini (high) for lower cost, both perform similarly on benchmarks, and Mistral Medium 3.1 for faster generation. For latency-sensitive apps, check the TTFT comparison above.