Nemotron 3 Super-120B-A12B vs ShieldGemma 9B
Nemotron 3 Super-120B-A12B (2026) and ShieldGemma 9B (2024) are compact production models from NVIDIA AI and Google DeepMind. Nemotron 3 Super-120B-A12B ships a 1M-token context window, while ShieldGemma 9B ships a 8K-token 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 Super-120B-A12B fits 131x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Super-120B-A12B | ShieldGemma 9B |
|---|---|---|
| Decision fit | RAG, Long context, and Classification | Classification |
| Context window | 1M | 8K |
| Cheapest output | $0.45/1M tokens | - |
| Provider routes | 4 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Nemotron 3 Super-120B-A12B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Nemotron 3 Super-120B-A12B has broader tracked provider coverage for fallback and procurement flexibility.
- Nemotron 3 Super-120B-A12B uniquely exposes Structured outputs in local model data.
- Local decision data tags Nemotron 3 Super-120B-A12B for RAG, Long context, and Classification.
- Local decision data tags ShieldGemma 9B for Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Nemotron 3 Super-120B-A12B
$185
Cheapest tracked route: OpenRouter
ShieldGemma 9B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Nemotron 3 Super-120B-A12B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-11 | 2024-07-01 |
| Context window | 1M | 8K |
| Parameters | 120B | 9B |
| Architecture | decoder only | decoder only |
| License | Unknown | 1 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Super-120B-A12B | ShieldGemma 9B |
|---|---|---|
| Input price | $0.09/1M tokens | - |
| Output price | $0.45/1M tokens | - |
| Providers |
Capabilities
| Capability | Nemotron 3 Super-120B-A12B | ShieldGemma 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Nemotron 3 Super-120B-A12B. 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 Super-120B-A12B has $0.09/1M input tokens and ShieldGemma 9B has no token price sourced yet. Provider availability is 4 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 Super-120B-A12B when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose ShieldGemma 9B 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 3 Super-120B-A12B or ShieldGemma 9B?
Nemotron 3 Super-120B-A12B supports 1M tokens, while ShieldGemma 9B supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Nemotron 3 Super-120B-A12B or ShieldGemma 9B open source?
Nemotron 3 Super-120B-A12B is listed under Unknown. ShieldGemma 9B is listed under 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 structured outputs, Nemotron 3 Super-120B-A12B or ShieldGemma 9B?
Nemotron 3 Super-120B-A12B 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 Super-120B-A12B and ShieldGemma 9B?
Nemotron 3 Super-120B-A12B is available on DeepInfra, NVIDIA NIM, OpenRouter, and Fireworks AI. ShieldGemma 9B is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Nemotron 3 Super-120B-A12B over ShieldGemma 9B?
Nemotron 3 Super-120B-A12B fits 131x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls. If your workload also depends on long-context analysis, start with Nemotron 3 Super-120B-A12B; if it depends on provider fit, run the same evaluation with ShieldGemma 9B.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.