Nemotron-Labs-Diffusion 3B vs Qwen3-105B
Nemotron-Labs-Diffusion 3B (2026) and Qwen3-105B (2025) are compact production models from NVIDIA AI and Alibaba. Nemotron-Labs-Diffusion 3B ships a 131k-token context window, while Qwen3-105B ships a 128k-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.
Nemotron-Labs-Diffusion 3B is safer overall; choose Qwen3-105B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Nemotron-Labs-Diffusion 3B | Qwen3-105B |
|---|---|---|
| Best for | general production evaluation | tool-calling agents |
| Decision fit | Long context | RAG, Agents, and Long context |
| Context window | 131k | 128k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Nemotron-Labs-Diffusion 3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Nemotron-Labs-Diffusion 3B for Long context.
- Qwen3-105B uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Qwen3-105B 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-Labs-Diffusion 3B
Unavailable
No complete token price in local provider data
Qwen3-105B
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-Labs-Diffusion 3B and Qwen3-105B; plan for SDK, billing, or endpoint changes.
- Qwen3-105B adds Function calling and Tool use in local capability data.
- No overlapping tracked provider route is sourced for Qwen3-105B and Nemotron-Labs-Diffusion 3B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-05-23 | 2025-12-15 |
| Context window | 131k | 128k |
| Parameters | 3B | 105B |
| Architecture | Decoder Only | - |
| License | NVIDIA Open Model | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | - | 2025-02 |
Pricing and availability
| Pricing attribute | Nemotron-Labs-Diffusion 3B | Qwen3-105B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Nemotron-Labs-Diffusion 3B | Qwen3-105B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on function calling: Qwen3-105B and tool use: Qwen3-105B. 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-Labs-Diffusion 3B has no token price sourced yet and Qwen3-105B 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-Labs-Diffusion 3B when long-context analysis and larger context windows are central to the workload. Choose Qwen3-105B when provider fit 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-Labs-Diffusion 3B or Qwen3-105B?
Nemotron-Labs-Diffusion 3B supports 131k tokens, while Qwen3-105B supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Is Nemotron-Labs-Diffusion 3B or Qwen3-105B open source?
Nemotron-Labs-Diffusion 3B is listed under NVIDIA Open Model. Qwen3-105B 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 function calling, Nemotron-Labs-Diffusion 3B or Qwen3-105B?
Qwen3-105B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Nemotron-Labs-Diffusion 3B or Qwen3-105B?
Qwen3-105B has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
When should I pick Nemotron-Labs-Diffusion 3B over Qwen3-105B?
Nemotron-Labs-Diffusion 3B is safer overall; choose Qwen3-105B when provider fit matters. If your workload also depends on long-context analysis, start with Nemotron-Labs-Diffusion 3B; if it depends on provider fit, run the same evaluation with Qwen3-105B.
Continue comparing
Last reviewed: 2026-06-20. Data sourced from public model cards and provider documentation.