Gemma 3n vs Nemotron 3 Nano Omni
Gemma 3n (2025) and Nemotron 3 Nano Omni (2026) are compact production models from Google DeepMind and NVIDIA AI. Gemma 3n ships a 32k-token context window, while Nemotron 3 Nano Omni 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.
Nemotron 3 Nano Omni fits 8x more tokens; pick it for long-context work and Gemma 3n for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 3n | Nemotron 3 Nano Omni |
|---|---|---|
| Best for | provider-routed production | multimodal apps |
| Decision fit | Classification and JSON / Tool use | Long context, Vision, and Classification |
| Context window | 32k | 262k |
| Cheapest output | - | - |
| Provider routes | 2 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3n has broader tracked provider coverage for fallback and procurement flexibility.
- Gemma 3n uniquely exposes Structured outputs in local model data.
- Local decision data tags Gemma 3n for Classification and JSON / Tool use.
- Nemotron 3 Nano Omni has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Nemotron 3 Nano Omni uniquely exposes Multimodal in local model data.
- Local decision data tags Nemotron 3 Nano Omni for Long context, Vision, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 3n
Unavailable
No complete token price in local provider data
Nemotron 3 Nano Omni
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 Gemma 3n and Nemotron 3 Nano Omni; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- Nemotron 3 Nano Omni adds Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Nemotron 3 Nano Omni and Gemma 3n; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Multimodal before moving production traffic.
- Gemma 3n adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-12 | 2026-04-28 |
| Context window | 32k | 262k |
| Parameters | — | 30B |
| Architecture | decoder only | Hybrid Mamba-Transformer MoE |
| License | Gemma | OpenMDW 1.1 |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Gemma 3n | Nemotron 3 Nano Omni |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers |
Pricing not yet sourced for either model.
Capabilities
| Capability | Gemma 3n | Nemotron 3 Nano Omni |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | 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 multimodal input: Nemotron 3 Nano Omni and structured outputs: Gemma 3n. 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: Gemma 3n has no token price sourced yet and Nemotron 3 Nano Omni has no token price sourced yet. Provider availability is 2 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 3n when provider fit and broader provider choice are central to the workload. Choose Nemotron 3 Nano Omni 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.
FAQ
Which has a larger context window, Gemma 3n or Nemotron 3 Nano Omni?
Nemotron 3 Nano Omni supports 262k tokens, while Gemma 3n supports 32k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 3n or Nemotron 3 Nano Omni open source?
Gemma 3n is listed under Gemma. Nemotron 3 Nano Omni is listed under OpenMDW 1.1. 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 multimodal input, Gemma 3n or Nemotron 3 Nano Omni?
Nemotron 3 Nano Omni 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.
Which is better for structured outputs, Gemma 3n or Nemotron 3 Nano Omni?
Gemma 3n has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemma 3n and Nemotron 3 Nano Omni?
Gemma 3n is available on Google AI Studio and GCP Vertex AI. Nemotron 3 Nano Omni is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3n over Nemotron 3 Nano Omni?
Nemotron 3 Nano Omni fits 8x more tokens; pick it for long-context work and Gemma 3n for tighter calls. If your workload also depends on provider fit, start with Gemma 3n; if it depends on long-context analysis, run the same evaluation with Nemotron 3 Nano Omni.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.