Nemotron 3 Nano vs ShieldGemma 2
Nemotron 3 Nano (2025) and ShieldGemma 2 (2024) are general-purpose language models from NVIDIA AI and Google DeepMind. Nemotron 3 Nano ships a 256K-token context window, while ShieldGemma 2 ships a not-yet-sourced context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Nemotron 3 Nano is safer overall; choose ShieldGemma 2 when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Nano | ShieldGemma 2 |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Agents, Vision, and Classification |
| 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.
- ShieldGemma 2 uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags ShieldGemma 2 for Agents, Vision, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Nemotron 3 Nano
Unavailable
No complete token price in local provider data
ShieldGemma 2
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 ShieldGemma 2; plan for SDK, billing, or endpoint changes.
- ShieldGemma 2 adds Vision, Multimodal, and Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for ShieldGemma 2 and Nemotron 3 Nano; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-15 | 2024-09-01 |
| Context window | 256K | — |
| Parameters | 3.97B | — |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0 | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Nano | ShieldGemma 2 |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers |
Pricing not yet sourced for either model.
Capabilities
| Capability | Nemotron 3 Nano | ShieldGemma 2 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: ShieldGemma 2, multimodal input: ShieldGemma 2, and structured outputs: ShieldGemma 2. 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 ShieldGemma 2 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 ShieldGemma 2 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. 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 ShieldGemma 2 open source?
Nemotron 3 Nano is listed under Apache 2.0. ShieldGemma 2 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 vision, Nemotron 3 Nano or ShieldGemma 2?
ShieldGemma 2 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 Nano or ShieldGemma 2?
ShieldGemma 2 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 function calling, Nemotron 3 Nano or ShieldGemma 2?
Both Nemotron 3 Nano and ShieldGemma 2 expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for tool use, Nemotron 3 Nano or ShieldGemma 2?
Both Nemotron 3 Nano and ShieldGemma 2 expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Nemotron 3 Nano and ShieldGemma 2?
Nemotron 3 Nano is available on NVIDIA NIM. ShieldGemma 2 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.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.