GPT-4o mini vs Mistral Large 2.1 vs Qwen2.5 72B Instruct

GPT-4o mini is the better all-round choice, scoring 56/100 against Qwen2.5 72B Instruct (40) and Mistral Large 2.1 (38). It leads on price and inputs & features. 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). Qwen2.5 72B Instruct costs $1.40 input / $5.60 output per million tokens (official Alibaba API price); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT-4o mini versus $2.45 for Qwen2.5 72B Instruct (9.3× as much) and $3.00 for Mistral Large 2.1 (11× as much).

Qwen2.5 72B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 72B Instruct 129.0 (#128 of 148), Mistral Large 2.1 128.5 (#130 of 148) and GPT-4o mini 126.6 (#135 of 148). The confidence ranges of the top two overlap (123.8–130.7 vs 123.8–130.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 72B Instruct 49.2%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, Mistral Large 2.1 7.8%, GPT-4o mini 6.9%.

There are no published SWE-bench Verified results for GPT-4o mini, Mistral Large 2.1 and Qwen2.5 72B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 72B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Mistral Large 2.1 and Qwen2.5 72B Instruct have the largest context windows (131,072 and 131,072 tokens), against 128,000 for GPT-4o mini. Maximum output per response: GPT-4o mini up to 16,384, Mistral Large 2.1 up to 16,384, Qwen2.5 72B Instruct up to 8,192 tokens.

GPT-4o mini accepts text, images and PDFs; Mistral Large 2.1 accepts text; Qwen2.5 72B Instruct accepts text. GPT-4o mini handles the widest range of inputs.

Mistral Large 2.1 and Qwen2.5 72B Instruct publishes its weights and can be self-hosted; GPT-4o mini is proprietary.

Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen2.5 72B Instruct came out Sep 19, 2024; GPT-4o mini came out Jul 18, 2024. Knowledge cutoff: GPT-4o mini Sep 2023, Mistral Large 2.1 Nov 2024, Qwen2.5 72B Instruct Apr 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.