Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Nemotron 3 Super 120B A12B (Reasoning) | Qwen3 30B A3B 2507 Instruct |
|---|---|---|
| Input ($/M tokens) | $0.2 | $0.2 |
| Output ($/M tokens) | $0.8 | $0.8 |
Verdict. Nemotron 3 Super 120B A12B (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, Qwen3 30B A3B 2507 Instruct is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3 30B A3B 2507 Instruct makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Nemotron 3 Super 120B A12B (Reasoning) is strongest on Coding Index (37.7), Intelligence Index (25.7). Qwen3 30B A3B 2507 Instruct leads on Intelligence Index (8.9).
Speed. Throughput is comparable — 144 tok/s vs 142 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
Provider. NVIDIA and Alibaba sell to overlapping but distinct developer audiences: NVIDIA tends to ship frontier reasoning models with premium positioning, while Alibaba 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 Super 120B A12B (Reasoning) costs $18.00 ($216/year); Qwen3 30B A3B 2507 Instruct costs $18.00 ($216/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Nemotron 3 Super 120B A12B (Reasoning) ≈ $2.60/run, Qwen3 30B A3B 2507 Instruct ≈ $2.60/run. At agent/realtime scale (200M input / 100M output per million requests): Nemotron 3 Super 120B A12B (Reasoning) ≈ $120/run, Qwen3 30B A3B 2507 Instruct ≈ $120/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.
Nemotron 3 Super 120B A12B (Reasoning) wins 2 out of 12 benchmarks compared to 0 for Qwen3 30B A3B 2507 Instruct. See the detailed benchmark chart above for per-category results.
Nemotron 3 Super 120B A12B (Reasoning) generates tokens faster at 144 tok/s vs 142 tok/s. Nemotron 3 Super 120B A12B (Reasoning) also has lower time-to-first-token (1.82s vs 1.87s).
Choose based on your priorities: both are similarly priced, Nemotron 3 Super 120B A12B (Reasoning) for stronger benchmark performance, and Nemotron 3 Super 120B A12B (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.