Llama-3.1-8B-Instruct vs Ministral 8B Instruct vs Qwen2.5 7B Instruct

It is close. Our weighted score puts them within a point (Qwen2.5 7B Instruct 42/100, Ministral 8B Instruct 42/100, Llama-3.1-8B-Instruct 42/100), so choose by what matters most for your work: Qwen2.5 7B Instruct for raw capability and Ministral 8B Instruct on price. 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). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); Qwen2.5 7B Instruct costs $0.175 input / $0.70 output per million tokens (official Alibaba 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 $0.156 for Llama-3.1-8B-Instruct (1× as much) and $0.306 for Qwen2.5 7B Instruct (2× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Qwen2.5 7B Instruct 35.5%, Ministral 8B Instruct 27.2% and Llama-3.1-8B-Instruct 27.0%. On individual benchmarks: GPQA Diamond — Qwen2.5 7B Instruct 35.5%, Ministral 8B Instruct 27.2%, Llama-3.1-8B-Instruct 27.0%.

There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, Ministral 8B Instruct and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 7B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Ministral 8B Instruct and Qwen2.5 7B Instruct have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Ministral 8B Instruct up to 8,192, Qwen2.5 7B Instruct up to 8,192 tokens.

Llama-3.1-8B-Instruct accepts text; Ministral 8B Instruct accepts text; Qwen2.5 7B Instruct accepts text. They handle the same number of input types.

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

Ministral 8B Instruct is the newest, released Oct 16, 2024. Qwen2.5 7B Instruct came out Sep 19, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, Qwen2.5 7B Instruct 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.