Mixtral 8x22B Instruct vs GPT-4o

GPT-4o is the better all-round choice, scoring 43/100 against Mixtral 8x22B Instruct (34). It leads on capability, inputs & features and context window. Mixtral 8x22B Instruct wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Mixtral 8x22B Instruct is cheaper at $2.00 input / $6.00 output per million tokens (median across 5 API providers). 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 Instruct versus $4.38 for GPT-4o (1.5× as much).

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#141 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). Their confidence ranges do not overlap (124.7–131.3 vs 115.7–124.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Mixtral 8x22B Instruct 34.1%.

There are no published SWE-bench Verified results for Mixtral 8x22B Instruct and GPT-4o 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 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Mixtral 8x22B Instruct up to 52,428, GPT-4o up to 16,384 tokens.

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

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

GPT-4o is the newest, released May 13, 2024. Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Instruct Jan 31, 2024, GPT-4o 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.