Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Mistral Small 3.1 | Gemma 4 12B (Non-reasoning) |
|---|---|---|
| Input ($/M tokens) | $0.1 | $0.1 |
| Output ($/M tokens) | $0.3 | $0.3 |
Verdict. Mistral Small 3.1 wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Gemma 4 12B (Non-reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Gemma 4 12B (Non-reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Mistral Small 3.1 is strongest on Coding Index (26.3), Intelligence Index (14.9). Gemma 4 12B (Non-reasoning) leads on Intelligence Index (13.2).
Speed. On throughput, Mistral Small 3.1 generates tokens at 138 tok/s versus 108 tok/s — about 22% faster. On time-to-first-token, Mistral Small 3.1 responds in 880ms vs 2380ms, which matters most for chat-style UIs.
Provider. Mistral and Google sell to overlapping but distinct developer audiences: Mistral tends to ship frontier reasoning models with premium positioning, while Google often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Mistral Small 3.1 costs $7.50 ($90/year); Gemma 4 12B (Non-reasoning) costs $7.50 ($90/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Small 3.1 ≈ $1.10/run, Gemma 4 12B (Non-reasoning) ≈ $1.10/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Small 3.1 ≈ $50/run, Gemma 4 12B (Non-reasoning) ≈ $50/run.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
Mistral Small 3.1 wins 2 out of 12 benchmarks compared to 0 for Gemma 4 12B (Non-reasoning). See the detailed benchmark chart above for per-category results.
Mistral Small 3.1 generates tokens faster at 138 tok/s vs 108 tok/s. Mistral Small 3.1 also has lower time-to-first-token (0.88s vs 2.38s).
Choose based on your priorities: both are similarly priced, Mistral Small 3.1 for stronger benchmark performance, and Mistral Small 3.1 for faster generation. For latency-sensitive apps, check the TTFT comparison above.