Mistral Medium 3.5 vs GPT-4.1 mini vs Qwen3 Max

GPT-4.1 mini is the better all-round choice, scoring 60/100 against Mistral Medium 3.5 (55) and Qwen3 Max (50). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba API price); Mistral Medium 3.5 costs $1.50 input / $7.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for GPT-4.1 mini versus $2.40 for Qwen3 Max (3.4× as much) and $3.00 for Mistral Medium 3.5 (4.3× as much).

Qwen3 Max scores higher on the Capabilities Index (ECI): Qwen3 Max 142.4 (#91 of 148), Mistral Medium 3.5 141.4 (#95 of 148) and GPT-4.1 mini 135.0 (#115 of 148). The confidence ranges of the top two overlap (140.0–144.6 vs 138.4–143.7), so treat the gap as small.

There are no published SWE-bench Verified results for Mistral Medium 3.5, GPT-4.1 mini and Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3 Max leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 262,144 for Mistral Medium 3.5 and 262,144 for Qwen3 Max. Maximum output per response: Mistral Medium 3.5 up to 262,144, GPT-4.1 mini up to 32,768, Qwen3 Max up to 65,536 tokens.

Mistral Medium 3.5 accepts text and images; GPT-4.1 mini accepts text, images and PDFs; Qwen3 Max accepts text. GPT-4.1 mini handles the widest range of inputs.

Mistral Medium 3.5 publishes its weights and can be self-hosted; GPT-4.1 mini and Qwen3 Max is proprietary.

Mistral Medium 3.5 is the newest, released Apr 29, 2026. Qwen3 Max came out Sep 23, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: GPT-4.1 mini Apr 2024, Qwen3 Max Apr 2025.

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.