Gemma 4 31B vs Ministral 3 8B 2512

Summary: In our 12-test suite Gemma 4 31B wins 8 tests, Ministral 3 8B 2512 wins 1, and 3 tests tie. Detailed walk-through (score format: Gemma vs Ministral, then rankings):

• structured output: Gemma 5 vs Ministral 4 — Gemma tied for 1st ("tied for 1st with 24 other models out of 54 tested"). This means Gemma is best suited for strict JSON/schema outputs and format adherence.
• strategic analysis: Gemma 5 vs Ministral 3 — Gemma tied for 1st ("tied for 1st with 25 other models out of 54 tested"); Ministral ranks 36/54. Gemma handles nuanced tradeoff reasoning with numbers better for decision-support tasks.
• creative problem solving: Gemma 4 vs Ministral 3 — Gemma rank 9/54 (21-model tie) vs Ministral rank 30/54. Gemma produces more specific, feasible ideas when creativity matters.
• tool calling: Gemma 5 vs Ministral 4 — Gemma tied for 1st ("tied for 1st with 16 other models out of 54 tested"); Ministral ranks 18/54. Gemma selects functions and constructs arguments more reliably for agentic workflows.
• faithfulness: Gemma 5 vs Ministral 4 — Gemma tied for 1st ("tied for 1st with 32 other models out of 55 tested"); Ministral rank 34/55. Gemma is less likely to hallucinate when sticking to source material.
• safety calibration: Gemma 2 vs Ministral 1 — Gemma rank 12/55 vs Ministral rank 32/55. Both score low on safety calibration overall, but Gemma refuses harmful prompts slightly more reliably in our tests.
• agentic planning: Gemma 5 vs Ministral 3 — Gemma tied for 1st ("tied for 1st with 14 other models out of 54 tested"); Ministral rank 42/54. Gemma is stronger at decomposing goals and recovery strategies.
• multilingual: Gemma 5 vs Ministral 4 — Gemma tied for 1st ("tied for 1st with 34 other models out of 55 tested"); Ministral rank 36/55. Gemma gives higher-equivalent quality in non-English languages.
• constrained rewriting: Gemma 4 vs Ministral 5 — Ministral tied for 1st ("tied for 1st with 4 other models out of 53 tested"); Gemma rank 6/53. Ministral compresses content into strict character limits better than Gemma.
• classification: 4 vs 4 (tie) — both tied for 1st with 29 others out of 53; both are equally reliable for routing/categorization.
• long context: 4 vs 4 (tie) — both rank 38/55; both handle 30K+ retrieval scenarios similarly in our testing.
• persona consistency: 5 vs 5 (tie) — both tied for 1st with 36 others out of 53; both maintain character and resist prompt injection well. Interpretation for real tasks: Gemma is the higher-quality, generalist choice when strict formatting, tool orchestration, faithfulness, planning, and multilingual support matter. Ministral's single clear win on constrained rewriting makes it a strong choice for tight-compression tasks and for teams that prioritize lower output costs.

Per-token pricing (per 1,000 tokens): Gemma 4 31B input $0.13, output $0.38; Ministral 3 8B 2512 input $0.15, output $0.15. For a balanced 50/50 input/output mix: 1M tokens (500k in / 500k out) costs Gemma $255 (500×$0.13 + 500×$0.38) vs Ministral $150 (500×$0.15 + 500×$0.15). At 10M tokens/month those totals scale to Gemma $2,550 vs Ministral $1,500. At 100M tokens/month Gemma $25,500 vs Ministral $15,000. For output-heavy workloads (all tokens are output): 1M output tokens cost Gemma $380 vs Ministral $150. The ~2.53× price ratio (Gemma more expensive overall) matters for high-volume deployments, consumer-facing chatbots, or generative-heavy services; smaller teams or prototypes likely benefit from Ministral's lower per-token output price.

Choose Gemma 4 31B if you need best-in-class structured outputs, tool calling, faithfulness, agentic planning, or multilingual quality and you can absorb higher per-token costs. Choose Ministral 3 8B 2512 if you must minimize per-token output spend (output $0.15/mk vs Gemma $0.38/mk) or if your workload prioritizes constrained rewriting and cost-efficiency at high volume.