Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Mistral Large 3 | GPT-4.1 mini |
|---|---|---|
| Input ($/M tokens) | $0.5 | $0.4 |
| Output ($/M tokens) | $1.5 | $1.6 |
Verdict. Mistral Large 3 and GPT-4.1 mini 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 0.9× the per-million-token cost, Mistral Large 3 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Large 3 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Mistral Large 3 is strongest on Coding Index (20.1), Intelligence Index (15.9). GPT-4.1 mini leads on Coding Index (20.2), Intelligence Index (14.8).
Speed. On throughput, GPT-4.1 mini generates tokens at 86 tok/s versus 48 tok/s — about 44% faster. On time-to-first-token, GPT-4.1 mini responds in 840ms vs 1170ms, 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 Large 3 costs $37.50 ($450/year); GPT-4.1 mini costs $36.00 ($432/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Large 3 ≈ $5.50/run, GPT-4.1 mini ≈ $5.20/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Large 3 ≈ $250/run, GPT-4.1 mini ≈ $240/run. GPT-4.1 mini 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-4.1 mini is cheaper overall. Its blended price (3:1 input/output ratio) is $0.70/M tokens vs $0.75/M for Mistral Large 3.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
GPT-4.1 mini generates tokens faster at 86 tok/s vs 48 tok/s. However, GPT-4.1 mini has lower time-to-first-token (0.84s vs 1.17s).
Choose based on your priorities: GPT-4.1 mini for lower cost, both perform similarly on benchmarks, and GPT-4.1 mini for faster generation. For latency-sensitive apps, check the TTFT comparison above.