Nemotron 3 Nano vs TxGemma
Nemotron 3 Nano (2025) and TxGemma (2024) are general-purpose language models from NVIDIA AI and Google DeepMind. Nemotron 3 Nano ships a 256k-token context window, while TxGemma ships a not-yet-sourced 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 is safer overall; choose TxGemma when provider fit matters.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Nano | TxGemma |
|---|---|---|
| Best for | tool-calling agents | tool-calling agents |
| Decision fit | RAG, Agents, and Long context | Agents, Classification, and JSON / Tool use |
| Context window | 256k | — |
| Cheapest output | - | - |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Nemotron 3 Nano has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Nemotron 3 Nano for RAG, Agents, and Long context.
- TxGemma uniquely exposes Structured outputs in local model data.
- Local decision data tags TxGemma for Agents, Classification, and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Nemotron 3 Nano
Unavailable
No complete token price in local provider data
TxGemma
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 Nano and TxGemma; plan for SDK, billing, or endpoint changes.
- TxGemma adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for TxGemma and Nemotron 3 Nano; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-15 | 2024-06-01 |
| Context window | 256k | — |
| Parameters | 3.97B | 2B |
| Architecture | mixture of experts | decoder only |
| License | NVIDIA Open Model | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Nano | TxGemma |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers |
Pricing not yet sourced for either model.
Capabilities
| Capability | Nemotron 3 Nano | TxGemma |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| 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 structured outputs: TxGemma. Both models share function calling and tool use, 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 Nano has no token price sourced yet and TxGemma has no token price sourced yet. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Nemotron 3 Nano when provider fit are central to the workload. Choose TxGemma 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
Is Nemotron 3 Nano or TxGemma open source?
Nemotron 3 Nano is listed under NVIDIA Open Model. TxGemma is listed under Proprietary. 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 3 Nano or TxGemma?
Both Nemotron 3 Nano and TxGemma expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for tool use, Nemotron 3 Nano or TxGemma?
Both Nemotron 3 Nano and TxGemma expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for structured outputs, Nemotron 3 Nano or TxGemma?
TxGemma 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 Nemotron 3 Nano and TxGemma?
Nemotron 3 Nano is available on NVIDIA NIM. TxGemma is available on GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick Nemotron 3 Nano over TxGemma?
Nemotron 3 Nano is safer overall; choose TxGemma when provider fit matters. If your workload also depends on provider fit, start with Nemotron 3 Nano; if it depends on provider fit, run the same evaluation with TxGemma.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.