GPT-4o mini vs Mixtral 8x7B

GPT-4o mini is the better all-round choice, scoring 56/100 against Mixtral 8x7B (37). It leads on capability, price, inputs & features and context window. 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). Mixtral 8x7B costs $0.70 input / $0.70 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 $0.70 for Mixtral 8x7B (2.7× as much).

GPT-4o mini scores higher on the Capabilities Index (ECI): GPT-4o mini 126.6 (#135 of 148) and Mixtral 8x7B 118.5 (#142 of 148). The confidence ranges of the top two overlap (120.5–128.5 vs 111.3–121.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o mini 37.7%, Mixtral 8x7B 30.6%.

There are no published SWE-bench Verified results for GPT-4o mini and Mixtral 8x7B yet, so there is no like-for-like coding score. On overall capability, GPT-4o mini leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-4o mini has the largest context window at 128,000 tokens, against 32,000 for Mixtral 8x7B. Maximum output per response: GPT-4o mini up to 16,384, Mixtral 8x7B up to 32,000 tokens.

GPT-4o mini accepts text, images and PDFs; Mixtral 8x7B accepts text. GPT-4o mini handles the widest range of inputs.

Mixtral 8x7B publishes its weights and can be self-hosted; GPT-4o mini is proprietary.

GPT-4o mini is the newest, released Jul 18, 2024. Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: GPT-4o mini Sep 2023, Mixtral 8x7B Jan 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.