Nemotron 3 Ultra vs Qwen3.5-4B
Nemotron 3 Ultra (2024) and Qwen3.5-4B (2026) are compact production models from NVIDIA AI and Alibaba. Nemotron 3 Ultra ships a 128k-token context window, while Qwen3.5-4B ships a 262k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-4B is safer overall; choose Nemotron 3 Ultra when provider fit matters.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Ultra | Qwen3.5-4B |
|---|---|---|
| Best for | general production evaluation | multimodal apps |
| Decision fit | Long context | Long context and Vision |
| Context window | 128k | 262k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Nemotron 3 Ultra for Long context.
- Qwen3.5-4B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-4B uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.5-4B for Long context and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Nemotron 3 Ultra
Unavailable
No complete token price in local provider data
Qwen3.5-4B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Nemotron 3 Ultra and Qwen3.5-4B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-4B adds Vision and Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-4B and Nemotron 3 Ultra; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-09-10 | 2026-03-02 |
| Context window | 128k | 262k |
| Parameters | 550B (55B active) | 4B |
| Architecture | decoder only | - |
| License | NVIDIA Open Model | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Ultra | Qwen3.5-4B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Nemotron 3 Ultra | Qwen3.5-4B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Qwen3.5-4B and multimodal input: Qwen3.5-4B. Both models share the core language-model surface, 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.
Pricing coverage is uneven: Nemotron 3 Ultra has no token price sourced yet and Qwen3.5-4B has no token price sourced yet. Provider availability is 0 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Nemotron 3 Ultra when provider fit are central to the workload. Choose Qwen3.5-4B when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Nemotron 3 Ultra or Qwen3.5-4B?
Qwen3.5-4B supports 262k tokens, while Nemotron 3 Ultra supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Nemotron 3 Ultra or Qwen3.5-4B open source?
Nemotron 3 Ultra is listed under NVIDIA Open Model. Qwen3.5-4B 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 Ultra or Qwen3.5-4B?
Qwen3.5-4B 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 Ultra or Qwen3.5-4B?
Qwen3.5-4B 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.
When should I pick Nemotron 3 Ultra over Qwen3.5-4B?
Qwen3.5-4B is safer overall; choose Nemotron 3 Ultra when provider fit matters. If your workload also depends on provider fit, start with Nemotron 3 Ultra; if it depends on long-context analysis, run the same evaluation with Qwen3.5-4B.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.