Mistral Medium 3.5 vs GPT-5.5 Instant

Mistral Medium 3.5 is the better all-round choice, scoring 55/100 against GPT-5.5 Instant (51). It leads on price. GPT-5.5 Instant wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Mistral Medium 3.5 is cheaper at $1.50 input / $7.50 output per million tokens (official Mistral API price). GPT-5.5 Instant costs $5.00 input / $30.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mistral Medium 3.5 versus $11.25 for GPT-5.5 Instant (3.8× as much).

GPT-5.5 Instant scores higher on the Capabilities Index (ECI): GPT-5.5 Instant 142.5 (#89 of 148) and Mistral Medium 3.5 141.4 (#95 of 148). The confidence ranges of the top two overlap (140.0–145.3 vs 138.4–143.7), so treat the gap as small.

There are no published SWE-bench Verified results for Mistral Medium 3.5 and GPT-5.5 Instant yet, so there is no like-for-like coding score. On overall capability, GPT-5.5 Instant leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-5.5 Instant has the largest context window at 400,000 tokens, against 262,144 for Mistral Medium 3.5. Maximum output per response: Mistral Medium 3.5 up to 262,144, GPT-5.5 Instant up to 128,000 tokens.

Mistral Medium 3.5 accepts text and images; GPT-5.5 Instant accepts text, images and PDFs. GPT-5.5 Instant handles the widest range of inputs.

Mistral Medium 3.5 publishes its weights and can be self-hosted; GPT-5.5 Instant is proprietary.

GPT-5.5 Instant is the newest, released May 5, 2026. Mistral Medium 3.5 came out Apr 29, 2026. Knowledge cutoff: GPT-5.5 Instant Dec 1, 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.