GPT-4o mini vs Mixtral 8x7B Instruct v0.1

GPT-4o mini is the better all-round choice, scoring 55/100 against Mixtral 8x7B Instruct v0.1 (34). 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 Instruct v0.1 costs $0.444 input / $0.579 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 $0.478 for Mixtral 8x7B Instruct v0.1 (1.8× as much).

GPT-4o mini scores higher on the Capabilities Index (ECI): GPT-4o mini 126.5 (#148 of 165) and Mixtral 8x7B Instruct v0.1 118.4 (#160 of 165). The confidence ranges of the top two overlap (120.5–128.6 vs 110.9–121.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o mini 37.7%, Mixtral 8x7B Instruct v0.1 30.6%.

There are no published SWE-bench Verified results for GPT-4o mini and Mixtral 8x7B Instruct v0.1 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. Note that Mixtral 8x7B Instruct v0.1 does not support tool calling, which most coding agents need.

GPT-4o mini has the largest context window at 128,000 tokens, against 32,768 for Mixtral 8x7B Instruct v0.1. Maximum output per response: GPT-4o mini up to 16,384, Mixtral 8x7B Instruct v0.1 up to 32,768 tokens.

GPT-4o mini accepts text, images and PDFs; Mixtral 8x7B Instruct v0.1 accepts text. GPT-4o mini handles the widest range of inputs.

Mixtral 8x7B Instruct v0.1 publishes its weights (Apache 2.0) and can be self-hosted; GPT-4o mini is proprietary.

GPT-4o mini is the newest, released Jul 18, 2024. Mixtral 8x7B Instruct v0.1 came out Dec 11, 2023. Knowledge cutoff: GPT-4o mini Sep 2023.

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 Nov 2, 2026.