Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen3.5 9B (Reasoning) | NVIDIA Nemotron Nano 9B V2 (Non-reasoning) |
|---|---|---|
| Input ($/M tokens) | $0.14 | $0.05 |
| Output ($/M tokens) | $0.2 | $0.2 |
Verdict. Qwen3.5 9B (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, NVIDIA Nemotron Nano 9B V2 (Non-reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). NVIDIA Nemotron Nano 9B V2 (Non-reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Qwen3.5 9B (Reasoning) is strongest on Coding Index (28.7), Intelligence Index (13.7). NVIDIA Nemotron Nano 9B V2 (Non-reasoning) leads on Intelligence Index (6.8).
Speed. On throughput, NVIDIA Nemotron Nano 9B V2 (Non-reasoning) generates tokens at 160 tok/s versus 90 tok/s — about 44% faster. On time-to-first-token, NVIDIA Nemotron Nano 9B V2 (Non-reasoning) responds in 1770ms vs 2130ms, which matters most for chat-style UIs.
Provider. Alibaba and NVIDIA sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while NVIDIA 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): Qwen3.5 9B (Reasoning) costs $7.20 ($86/year); NVIDIA Nemotron Nano 9B V2 (Non-reasoning) costs $4.50 ($54/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3.5 9B (Reasoning) ≈ $1.10/run, NVIDIA Nemotron Nano 9B V2 (Non-reasoning) ≈ $0.65/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3.5 9B (Reasoning) ≈ $48/run, NVIDIA Nemotron Nano 9B V2 (Non-reasoning) ≈ $30/run. NVIDIA Nemotron Nano 9B V2 (Non-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
NVIDIA Nemotron Nano 9B V2 (Non-reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.09/M tokens vs $0.15/M for Qwen3.5 9B (Reasoning).
Qwen3.5 9B (Reasoning) wins 2 out of 12 benchmarks compared to 0 for NVIDIA Nemotron Nano 9B V2 (Non-reasoning). See the detailed benchmark chart above for per-category results.
NVIDIA Nemotron Nano 9B V2 (Non-reasoning) generates tokens faster at 160 tok/s vs 90 tok/s. However, NVIDIA Nemotron Nano 9B V2 (Non-reasoning) has lower time-to-first-token (1.77s vs 2.13s).
Choose based on your priorities: NVIDIA Nemotron Nano 9B V2 (Non-reasoning) for lower cost, Qwen3.5 9B (Reasoning) for stronger benchmark performance, and NVIDIA Nemotron Nano 9B V2 (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.