Gemma 4 31B vs Mistral Large 3 2512

We ran both models across our 12-test suite and Gemma 4 31B wins the majority (8 wins, 0 losses, 4 ties). Detailed comparison: - Strategic analysis: Gemma 5 vs Mistral 4 (Gemma tied for 1st with 25 others out of 54). This indicates Gemma gives stronger nuanced tradeoff reasoning for numeric decisions. - Tool calling: Gemma 5 vs Mistral 4 (Gemma tied for 1st with 16 others; Mistral rank 18 of 54). Gemma is more reliable at function selection, argument accuracy, and sequencing. - Creative problem solving: Gemma 4 vs Mistral 3 (Gemma rank 9 of 54 vs Mistral rank 30) — Gemma produces more non-obvious, specific ideas in our tests. - Classification: Gemma 4 vs Mistral 3 (Gemma tied for 1st with 29 others; Mistral rank 31) — Gemma is stronger at routing and labeling tasks. - Persona consistency: Gemma 5 vs Mistral 3 (Gemma tied for 1st; Mistral rank 45) — Gemma maintains character and resists injection better in our evaluations. - Agentic planning: Gemma 5 vs Mistral 4 (Gemma tied for 1st; Mistral rank 16) — Gemma better at goal decomposition and recovery. - Constrained rewriting: Gemma 4 vs Mistral 3 (Gemma rank 6 of 53 vs Mistral rank 31) — Gemma handles tight character limits more precisely. - Safety calibration: Gemma 2 vs Mistral 1 (Gemma rank 12 vs Mistral rank 32) — Gemma is more likely to refuse harmful requests while permitting legitimate ones in our tests. Ties (no clear winner): structured output 5/5 (both tied for 1st), faithfulness 5/5 (both tied for 1st), long context 4/4 (both rank 38 of 55), multilingual 5/5 (both tied for 1st). Practical meaning: Gemma is demonstrably stronger for planning, tool orchestration, persona-sensitive and classification-heavy flows; Mistral is competitive on schema compliance, sticking to sources, long-context retrieval, and multilingual outputs but does not outperform Gemma on any single test in our suite.

Per-mtok rates (1 mtok = 1,000 tokens): Gemma 4 31B charges $0.13 input + $0.38 output = $0.51/mtok. Mistral Large 3 2512 charges $0.50 input + $1.50 output = $2.00/mtok. Assuming a 50/50 split of input/output tokens, monthly costs: 1M tokens (1,000 mtok) = Gemma $510 vs Mistral $2,000; 10M = Gemma $5,100 vs Mistral $20,000; 100M = Gemma $51,000 vs Mistral $200,000. The gap matters for high-volume apps (chatbots, large-scale inference, SaaS) where Mistral adds tens to hundreds of thousands of dollars per month; for very low-volume or experimental use the delta may be acceptable.

Choose Gemma 4 31B if you need: - Better tool calling and agentic planning (tool calling 5 vs 4; agentic planning 5 vs 4), - Stronger persona consistency and classification (persona consistency 5 vs 3; classification 4 vs 3), - Much lower inference cost (combined $0.51/mtok vs $2.00/mtok). Choose Mistral Large 3 2512 if you need: - The specific architecture or license Mistral offers (description notes a sparse MoE design and Apache 2.0 license in the payload) and are willing to pay ~4x the per-token cost; or - You value parity on structured output, faithfulness, long-context, or multilingual performance (those tests tie).