GPT-4o mini vs Mistral Small 3.1 24B

It is close. Our weighted score puts them within 1 points (GPT-4o mini 56/100, Mistral Small 3.1 24B 55/100), so choose by what matters most for your work: Mistral Small 3.1 24B for raw capability and GPT-4o mini on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GPT-4o mini is cheaper at $0.15 input / $0.60 output per million tokens (official OpenAI API price). Mistral Small 3.1 24B costs $0.229 input / $0.436 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT-4o mini versus $0.281 for Mistral Small 3.1 24B (1.1× as much).

Mistral Small 3.1 24B scores higher on the Capabilities Index (ECI): Mistral Small 3.1 24B 127.5 (#132 of 148) and GPT-4o mini 126.6 (#135 of 148). The confidence ranges of the top two overlap (122.6–129.4 vs 120.5–128.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — GPT-4o mini 6.9%, Mistral Small 3.1 24B 5.8%.

There are no published SWE-bench Verified results for GPT-4o mini and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.1 24B leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-4o mini and Mistral Small 3.1 24B share the same 128,000-token context window. Maximum output per response: GPT-4o mini up to 16,384, Mistral Small 3.1 24B up to 16,384 tokens.

GPT-4o mini accepts text, images and PDFs; Mistral Small 3.1 24B accepts text and images. GPT-4o mini handles the widest range of inputs.

Mistral Small 3.1 24B publishes its weights and can be self-hosted; GPT-4o mini is proprietary.

Mistral Small 3.1 24B is the newest, released Mar 17, 2025. GPT-4o mini came out Jul 18, 2024. Knowledge cutoff: GPT-4o mini Sep 2023, Mistral Small 3.1 24B Jun 2024.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.