Nemotron 3 Super-120B-A12B vs Qwen3.5-9B
Nemotron 3 Super-120B-A12B (2026) and Qwen3.5-9B (2026) are general-purpose language models from NVIDIA AI and Alibaba. Nemotron 3 Super-120B-A12B ships a 1.05m-token context window, while Qwen3.5-9B ships a 262k-token context window. On Google-Proof Q&A, Qwen3.5-9B leads by 1.7 pts. On pricing, Nemotron 3 Super-120B-A12B costs $0.09/1M input tokens versus $0.10/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Nemotron 3 Super-120B-A12B fits 4x more tokens; pick it for long-context work and Qwen3.5-9B for tighter calls.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Super-120B-A12B | Qwen3.5-9B |
|---|---|---|
| Best for | long-context analysis and provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | RAG, Long context, and Classification | RAG, Agents, and Long context |
| Context window | 1.05m | 262k |
| Cheapest output | $0.45/1M tokens | $0.15/1M tokens |
| Provider routes | 6 tracked | 3 tracked |
| Shared benchmarks | 1 rows | Google-Proof Q&A leader |
Decision tradeoffs
- Nemotron 3 Super-120B-A12B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Nemotron 3 Super-120B-A12B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Nemotron 3 Super-120B-A12B for RAG, Long context, and Classification.
- Qwen3.5-9B leads the largest shared benchmark signal on Google-Proof Q&A by 1.7 points.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Nemotron 3 Super-120B-A12B
$185
Cheapest tracked route/tier: OpenRouter
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $67.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3.5-9B is $0.30/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Nemotron 3 Super-120B-A12B is $0.30/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-11 | 2026-03-02 |
| Context window | 1.05m | 262k |
| Parameters | 120B | 9B |
| Architecture | decoder only | decoder only |
| License | NVIDIA Open Model | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Super-120B-A12B | Qwen3.5-9B |
|---|---|---|
| Input price | $0.09/1M tokens | $0.10/1M tokens |
| Output price | $0.45/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Nemotron 3 Super-120B-A12B | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Nemotron 3 Super-120B-A12B | Qwen3.5-9B |
|---|---|---|
| Google-Proof Q&A | 80.0 | 81.7 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Nemotron 3 Super-120B-A12B at 80 and Qwen3.5-9B at 81.7, with Qwen3.5-9B ahead by 1.7 points. The largest visible gap is 1.7 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Qwen3.5-9B, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, and tool use: Qwen3.5-9B. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Nemotron 3 Super-120B-A12B lists $0.09/1M input and $0.45/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $0.08 per million blended tokens. Availability is 6 providers versus 3, so concentration risk also matters.
Choose Nemotron 3 Super-120B-A12B when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Qwen3.5-9B when vision-heavy evaluation are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Nemotron 3 Super-120B-A12B or Qwen3.5-9B?
Nemotron 3 Super-120B-A12B supports 1.05m tokens, while Qwen3.5-9B supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Nemotron 3 Super-120B-A12B or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Nemotron 3 Super-120B-A12B costs $0.09/1M input and $0.45/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Nemotron 3 Super-120B-A12B or Qwen3.5-9B open source?
Nemotron 3 Super-120B-A12B is listed under NVIDIA Open Model. Qwen3.5-9B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Nemotron 3 Super-120B-A12B or Qwen3.5-9B?
Qwen3.5-9B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Nemotron 3 Super-120B-A12B or Qwen3.5-9B?
Qwen3.5-9B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Nemotron 3 Super-120B-A12B and Qwen3.5-9B?
Nemotron 3 Super-120B-A12B is available on Cloudflare Workers AI, DeepInfra, NVIDIA NIM, OpenRouter, and Fireworks AI. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-01. Data sourced from public model cards and provider documentation.