Mixtral 8x7B vs Ministral 8B Instruct

Ministral 8B Instruct is the better all-round choice, scoring 42/100 against Mixtral 8x7B (33). It leads on price and context window. Mixtral 8x7B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.

Ministral 8B Instruct is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). 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 $0.15 per million tokens for Ministral 8B Instruct versus $0.70 for Mixtral 8x7B (4.7× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Mixtral 8x7B 30.6% and Ministral 8B Instruct 27.2%. On individual benchmarks: GPQA Diamond — Mixtral 8x7B 30.6%, Ministral 8B Instruct 27.2%.

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

Ministral 8B Instruct has the largest context window at 131,072 tokens, against 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x7B up to 32,000, Ministral 8B Instruct up to 8,192 tokens.

Mixtral 8x7B accepts text; Ministral 8B Instruct accepts text. They handle the same number of input types.

Yes, both publish their weights (Mistral Research License), so you can self-host them.

Ministral 8B Instruct is the newest, released Oct 16, 2024. Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: 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.