Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| Input ($/M tokens) | $0.4 | $0.5 |
| Output ($/M tokens) | $1.6 | $1.5 |
Verdict. GPT-4.1 mini and Mistral Large 3 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 1.1× 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. GPT-4.1 mini is strongest on Coding Index (20.2), Intelligence Index (14.8). Mistral Large 3 leads on Coding Index (20.1), Intelligence Index (15.9).
Speed. Throughput is comparable — 79 tok/s vs 78 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
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-4.1 mini costs $36.00 ($432/year); Mistral Large 3 costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-4.1 mini ≈ $5.20/run, Mistral Large 3 ≈ $5.50/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-4.1 mini ≈ $240/run, Mistral Large 3 ≈ $250/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 79 tok/s vs 78 tok/s. GPT-4.1 mini also has lower time-to-first-token (0.93s vs 1.11s).
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.