Mixtral 8x7B Instruct v0.1 vs WizardLM 2 8x22B

WizardLM 2 8x22B is the better all-round choice, scoring 38/100 against Mixtral 8x7B Instruct v0.1 (31). It leads on capability and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because WizardLM 2 8x22B has no Capabilities Index score yet.

Mixtral 8x7B Instruct v0.1 is cheaper at $0.444 input / $0.579 output per million tokens (median across 2 API providers). WizardLM 2 8x22B costs $0.493 input / $0.493 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.478 per million tokens for Mixtral 8x7B Instruct v0.1 versus $0.493 for WizardLM 2 8x22B (1× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): WizardLM 2 8x22B 43.4% and Mixtral 8x7B Instruct v0.1 30.6%. On individual benchmarks: GPQA Diamond — WizardLM 2 8x22B 43.4%, Mixtral 8x7B Instruct v0.1 30.6%.

There are no published SWE-bench Verified results for Mixtral 8x7B Instruct v0.1 and WizardLM 2 8x22B yet, so there is no like-for-like coding score. On overall capability, WizardLM 2 8x22B leads, which tends to carry over to coding, but test on your own codebase. Note that Mixtral 8x7B Instruct v0.1 and WizardLM 2 8x22B does not support tool calling, which most coding agents need.

WizardLM 2 8x22B has the largest context window at 65,536 tokens, against 32,768 for Mixtral 8x7B Instruct v0.1. Maximum output per response: Mixtral 8x7B Instruct v0.1 up to 32,768, WizardLM 2 8x22B up to 8,000 tokens.

Mixtral 8x7B Instruct v0.1 accepts text; WizardLM 2 8x22B accepts text. They handle the same number of input types.

Yes, both publish their weights (Apache 2.0 and Apache-2.0), so you can self-host them.

WizardLM 2 8x22B is the newest, released Apr 15, 2024. Mixtral 8x7B Instruct v0.1 came out Dec 11, 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.