GPT-4o vs Mixtral 8x22B

GPT-4o is the better all-round choice, scoring 43/100 against Mixtral 8x22B (33). It leads on capability, inputs & features and context window. Mixtral 8x22B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Mixtral 8x22B is cheaper at $2.00 input / $6.00 output per million tokens (official Mistral API price). GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mixtral 8x22B versus $4.38 for GPT-4o (1.5× as much).

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148) and Mixtral 8x22B 122.0 (#139 of 148). The confidence ranges of the top two overlap (124.2–131.5 vs 115.1–124.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Mixtral 8x22B 34.1%.

There are no published SWE-bench Verified results for GPT-4o and Mixtral 8x22B yet, so there is no like-for-like coding score. On overall capability, GPT-4o leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-4o has the largest context window at 128,000 tokens, against 64,000 for Mixtral 8x22B. Maximum output per response: GPT-4o up to 16,384, Mixtral 8x22B up to 64,000 tokens.

GPT-4o accepts text, images and PDFs; Mixtral 8x22B accepts text. GPT-4o handles the widest range of inputs.

Mixtral 8x22B publishes its weights and can be self-hosted; GPT-4o is proprietary.

GPT-4o is the newest, released May 13, 2024. Mixtral 8x22B came out Apr 17, 2024. Knowledge cutoff: GPT-4o Sep 2023, Mixtral 8x22B 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.