Key differences
- Throughput: ~3.3× Qwen3-30B on H200 (8K→16K).
- Context: Nemotron 1M vs Qwen3 typical 32k/128k.
- Control: Reasoning ON/OFF + thinking budgets vs standard chat.
Model comparison
Nemotron 3 vs Qwen3: Throughput, Context, and Control
Nemotron 3 Nano 30B offers ~3.3× Qwen3-30B throughput on H200, a 1M context window, and Reasoning ON/OFF with budgets for cost control.
nemotron 3 vs qwen3qwen3 comparisonnemotron throughputnemotron 1m context
When to pick which
- High-concurrency agents → Nemotron 3 for lower latency/cost.
- Long-document/RAG → Nemotron 1M context for multi-doc fusion.
- Tool use → both work; Nemotron adds budgets to tame cost.
Migration tips
- Keep function schemas identical to swap models easily.
- Set thinking budgets for long chains to avoid token blowup.
FAQ
Why is Nemotron faster?
Sparse MoE lowers active compute per token while keeping reasoning strength.
Does Qwen3 have long context?
Extended variants exist, but default windows are shorter; Nemotron ships 1M.
Is migration costly?
API-compatible with vLLM/SGLang—keep prompts and tool schemas, then switch models.