Gemma 3 4B IT vs Ministral 8B Instruct

Gemma 3 4B IT is the better all-round choice, scoring 47/100 against Ministral 8B Instruct (42). It leads on price and inputs & features. Ministral 8B Instruct 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.

Gemma 3 4B IT is cheaper at $0.05 input / $0.10 output per million tokens (median across 7 API providers). Ministral 8B Instruct costs $0.15 input / $0.15 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Gemma 3 4B IT versus $0.15 for Ministral 8B Instruct (2.4× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Ministral 8B Instruct 27.2% and Gemma 3 4B IT 23.2%. On individual benchmarks: GPQA Diamond — Ministral 8B Instruct 27.2%, Gemma 3 4B IT 23.2%.

There are no published SWE-bench Verified results for Gemma 3 4B IT and Ministral 8B Instruct yet, so there is no like-for-like coding score. On overall capability, Ministral 8B Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Gemma 3 4B IT and Ministral 8B Instruct share the same 131,072-token context window. Maximum output per response: Gemma 3 4B IT up to 131,072, Ministral 8B Instruct up to 8,192 tokens.

Gemma 3 4B IT accepts text and images; Ministral 8B Instruct accepts text. Gemma 3 4B IT handles the widest range of inputs.

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

Gemma 3 4B IT is the newest, released Mar 12, 2025. Ministral 8B Instruct came out Oct 16, 2024. Knowledge cutoff: Gemma 3 4B IT Aug 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.