Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Nemotron 3 Nano Omni 30B A3B Reasoning | Mistral Small 3.2 |
|---|---|---|
| Input ($/M tokens) | $0.07 | $0.1 |
| Output ($/M tokens) | $0.3 | $0.3 |
Verdict. Nemotron 3 Nano Omni 30B A3B Reasoning 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, Mistral Small 3.2 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Small 3.2 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Nemotron 3 Nano Omni 30B A3B Reasoning is strongest on Intelligence Index (15.0), Coding Index (13.8). Mistral Small 3.2 leads on Coding Index (12.5), Intelligence Index (10.7).
Speed. On throughput, Nemotron 3 Nano Omni 30B A3B Reasoning generates tokens at 328 tok/s versus 140 tok/s — about 57% faster. On time-to-first-token, Mistral Small 3.2 responds in 830ms vs 1090ms, which matters most for chat-style UIs.
Provider. NVIDIA and Mistral sell to overlapping but distinct developer audiences: NVIDIA tends to ship frontier reasoning models with premium positioning, while Mistral 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): Nemotron 3 Nano Omni 30B A3B Reasoning costs $6.60 ($79/year); Mistral Small 3.2 costs $7.50 ($90/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Nemotron 3 Nano Omni 30B A3B Reasoning ≈ $0.95/run, Mistral Small 3.2 ≈ $1.10/run. At agent/realtime scale (200M input / 100M output per million requests): Nemotron 3 Nano Omni 30B A3B Reasoning ≈ $44/run, Mistral Small 3.2 ≈ $50/run. Nemotron 3 Nano Omni 30B A3B Reasoning becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
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.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper overall. Its blended price (3:1 input/output ratio) is $0.13/M tokens vs $0.15/M for Mistral Small 3.2.
Nemotron 3 Nano Omni 30B A3B Reasoning wins 2 out of 12 benchmarks compared to 0 for Mistral Small 3.2. See the detailed benchmark chart above for per-category results.
Nemotron 3 Nano Omni 30B A3B Reasoning generates tokens faster at 328 tok/s vs 140 tok/s. However, Mistral Small 3.2 has lower time-to-first-token (0.83s vs 1.09s).
Choose based on your priorities: Nemotron 3 Nano Omni 30B A3B Reasoning for lower cost, Nemotron 3 Nano Omni 30B A3B Reasoning for stronger benchmark performance, and Nemotron 3 Nano Omni 30B A3B Reasoning for faster generation. For latency-sensitive apps, check the TTFT comparison above.