Gemma 4 31B vs Mistral Small 3.1 24B

Summary: Gemma 4 31B wins 11 benchmarks in our 12-test suite; Mistral Small 3.1 24B wins only long context. Detailed walk-through by test (Gemma score vs Mistral score, with ranking context and practical meaning):

• tool calling: Gemma 5 vs Mistral 1. Gemma is tied for 1st (tied with 16 others of 54) for correct function selection, argument accuracy and sequencing. Mistral ranks 53 of 54 and its quirks include no_tool calling=true, so Mistral is effectively unsuitable for tool-based agent workflows in our tests.

• strategic analysis: Gemma 5 vs Mistral 3. Gemma is tied for 1st (tied with 25 others of 54) on nuanced tradeoff reasoning; expect better numeric tradeoffs and multi-step decision advice from Gemma.

• structured output: Gemma 5 vs Mistral 4. Gemma is tied for 1st (tied with 24 others) on schema/JSON compliance; Mistral ranks 26 of 54. Use Gemma when strict format adherence is required.

• faithfulness: Gemma 5 vs Mistral 4. Gemma ranks tied for 1st (tied with 32 others of 55) on sticking to source material; this reduces hallucination risk relative to Mistral in our tests.

• classification: Gemma 4 vs Mistral 3. Gemma tied for 1st (tied with 29 others of 53), so routing and categorization tasks were more accurate in our testing.

• persona consistency: Gemma 5 vs Mistral 2. Gemma tied for 1st (tied with 36 others of 53); Mistral ranks 51 of 53, meaning Gemma better maintains character and resists prompt injection in role-based chat.

• multilingual: Gemma 5 vs Mistral 4. Gemma tied for 1st (tied with 34 others of 55); expect higher-quality non-English outputs from Gemma in our suite.

• agentic planning: Gemma 5 vs Mistral 3. Gemma tied for 1st (tied with 14 others of 54) for decomposition, fallback and recovery — important for multi-step agents.

• constrained rewriting: Gemma 4 vs Mistral 3. Gemma ranked 6 of 53 (25 models share this score) on tight-character rewrites, so better at strict-length edits.

• creative problem solving: Gemma 4 vs Mistral 2. Gemma ranks 9 of 54 (21 models share) on producing non-obvious, feasible ideas; Mistral scored lower here.

• safety calibration: Gemma 2 vs Mistral 1. Gemma ranks 12 of 55 (20 share) and Mistral ranks 32 of 55; Gemma is better at refusing harmful requests while permitting legitimate ones in our tests.

• long context: Gemma 4 vs Mistral 5. This is Mistral’s only win; Mistral is tied for 1st (tied with 36 others of 55) for retrieval accuracy at 30K+ tokens. If your workload is heavy long-context retrieval, Mistral has the edge.

Practical takeaway: Gemma dominates in agentic, structured, multilingual and safety-sensitive tasks and is also cheaper. Mistral’s single advantage is long-context retrieval accuracy.

Costs per mTok: Gemma 4 31B input $0.13 / output $0.38; Mistral Small 3.1 24B input $0.35 / output $0.56. Assuming a balanced 50/50 split of input/output tokens, monthly cost examples: • 1M tokens (1,000 mTok): Gemma ≈ $255; Mistral ≈ $455. • 10M tokens (10,000 mTok): Gemma ≈ $2,550; Mistral ≈ $4,550. • 100M tokens (100,000 mTok): Gemma ≈ $25,500; Mistral ≈ $45,500. Gemma runs at ~0.68x the cost of Mistral overall (priceRatio 0.6786). High-volume inference, large-scale chatbots, and API-driven products that generate lots of output tokens should care about this gap — at 100M tokens/month the difference is roughly $20k/month. If your workload is dominated by very long-context reads (30K+ tokens) and you can’t accept the lack of tool calling, Mistral’s premium may be defensible; otherwise Gemma gives better value.

Choose Gemma 4 31B if: • You need tool calling / agent workflows (Gemma tool calling 5 vs Mistral 1; Mistral has no_tool calling quirk). • You require strict structured output, high faithfulness, persona consistency, multilingual support, or strategic analysis (Gemma wins these tests and often ranks tied for 1st). • You run high-volume inference and want lower per-token costs (Gemma $0.13 in/$0.38 out vs Mistral $0.35/$0.56).

Choose Mistral Small 3.1 24B if: • Your primary need is best-in-class long-context retrieval at 30K+ tokens (Mistral long context 5 vs Gemma 4; Mistral tied for 1st). • You can tolerate no tool calling and higher costs for that specific long-context advantage.