Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Mistral Medium 3.1 | GPT-5 mini (high) |
|---|---|---|
| Input ($/M tokens) | $0.4 | $0.25 |
| Output ($/M tokens) | $2 | $2 |
Verdict. Mistral Medium 3.1 and GPT-5 mini (high) 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, GPT-5 mini (high) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5 mini (high) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Mistral Medium 3.1 is strongest on Coding Index (20.5), Intelligence Index (14.7). GPT-5 mini (high) leads on Intelligence Index (25.8), Coding Index (15.6).
Speed. On throughput, Mistral Medium 3.1 generates tokens at 106 tok/s versus 83 tok/s — about 22% faster. On time-to-first-token, Mistral Medium 3.1 responds in 1470ms vs 89370ms, which matters most for chat-style UIs.
Provider. Mistral and OpenAI sell to overlapping but distinct developer audiences: Mistral tends to ship frontier reasoning models with premium positioning, while OpenAI 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): Mistral Medium 3.1 costs $42.00 ($504/year); GPT-5 mini (high) costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Medium 3.1 ≈ $6.00/run, GPT-5 mini (high) ≈ $5.25/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Medium 3.1 ≈ $280/run, GPT-5 mini (high) ≈ $250/run. GPT-5 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 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 83 tok/s. Mistral Medium 3.1 also has lower time-to-first-token (1.47s vs 89.37s).
Choose based on your priorities: GPT-5 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.