Gemma 4 26B A4B vs Mistral Small 3.2 24B

Summary of our 12-test head-to-head (scores on our 1–5 scale): Gemma wins 9 tests, Mistral wins 1, and 2 are ties. Detailed walk-through: • Structured output — Gemma 5 vs Mistral 4. Gemma is tied for 1st (tied with 24 others) on JSON/schema compliance in our tests; pick Gemma when strict format adherence matters. • Strategic analysis — Gemma 5 vs Mistral 2. Gemma ties for 1st (with 25 others), meaning it handles nuanced tradeoffs and numeric reasoning significantly better in our benchmarks. • Creative problem solving — Gemma 4 vs Mistral 2. Gemma ranks 9 of 54 vs Mistral 47 of 54; expect more specific, feasible ideas from Gemma. • Tool calling — Gemma 5 vs Mistral 4. Gemma is tied for 1st (with 16 models); in our tests it better chooses functions, argument accuracy, and sequencing. • Faithfulness — Gemma 5 vs Mistral 4. Gemma is tied for 1st (with 32 others); it more reliably sticks to source material in our evaluations. • Classification — Gemma 4 vs Mistral 3. Gemma tied for 1st (with 29 others); better routing and labeling in our tests. • Long context — Gemma 5 vs Mistral 4. Gemma tied for 1st (with 36 others) and also has a larger context window (262,144 vs 128,000), improving retrieval accuracy at 30k+ tokens in our scenarios. • Persona consistency — Gemma 5 vs Mistral 3. Gemma tied for 1st (with 36 others); it holds character and resists injection better in our tests. • Multilingual — Gemma 5 vs Mistral 4. Gemma tied for 1st (with 34 others); higher-quality non-English outputs in our benchmarks. • Constrained rewriting — Gemma 3 vs Mistral 4. Mistral wins this one and ranks 6 of 53 (vs Gemma rank 31): Mistral is better at tight compression and exact character-limit rewrites. • Ties: Safety calibration — both score 1 (rank 32 of 55, tied with 23 others): both models showed similar refusal/permissiveness behavior in our test suite. Agentic planning — both score 4 and share the same rank (16 of 54 with many ties): comparable goal decomposition and failure recovery in our tests. Practical meaning: Gemma is the higher-quality choice for schema outputs, tool integrations, long-context tasks, multilingual and faithful responses. Mistral’s clear advantage is constrained-rewriting and a lower output price, making it better for budgeted, compression, or tight-format workloads.

Per-token rates (per mTok = per 1,000 tokens): Gemma input $0.08 / output $0.35; Mistral input $0.075 / output $0.20. Using a 50/50 input/output split: • 1M tokens/month: Gemma ≈ $215, Mistral ≈ $137.50 (Gemma +$77.50) • 10M tokens/month: Gemma ≈ $2,150, Mistral ≈ $1,375 (+$775) • 100M tokens/month: Gemma ≈ $21,500, Mistral ≈ $13,750 (+$7,750). If your workload is output-heavy (e.g., 80% output tokens), the gap widens because Gemma's output rate is $0.35 vs Mistral's $0.20. Teams with high-volume inference, tight margins, or consumer-scale chat should care most about the gap; teams prioritizing top fidelity for complex structured outputs or long-context tasks may accept the higher cost.

Choose Gemma 4 26B A4B if: • You need top-tier structured output (5/5), tool calling (5/5), long-context retrieval (5/5), faithfulness (5/5), or high-quality multilingual and persona consistency. Gemma also offers a 262,144-token window and more instruction-tuning parameters (e.g., include_reasoning, reasoning). Accept higher cost ($0.35/output mTok) for better format fidelity and complex reasoning. Choose Mistral Small 3.2 24B if: • You are cost-sensitive (output $0.20/mTok), require better constrained rewriting (Mistral 4 vs Gemma 3; Mistral ranks 6 of 53), or run very high-volume inference where the per-mTok gap multiplies. Mistral still scores competently on tool calling and agentic planning but trails on creative problem solving, strategic analysis, and long-context.