Llama Guard 2 8B vs Nemotron 3 Ultra
Llama Guard 2 8B (2024) and Nemotron 3 Ultra (2024) are compact production models from AI at Meta and NVIDIA AI. Llama Guard 2 8B ships a 8k-token context window, while Nemotron 3 Ultra 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.
Nemotron 3 Ultra fits 16x more tokens; pick it for long-context work and Llama Guard 2 8B for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama Guard 2 8B | Nemotron 3 Ultra |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Classification | Long context |
| Context window | 8k | 128k |
| Cheapest output | $0.25/1M tokens | - |
| Provider routes | 3 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama Guard 2 8B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama Guard 2 8B for Classification.
- Nemotron 3 Ultra has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Nemotron 3 Ultra for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama Guard 2 8B
$103
Cheapest tracked route/tier: Replicate API
Nemotron 3 Ultra
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 Llama Guard 2 8B and Nemotron 3 Ultra; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Nemotron 3 Ultra and Llama Guard 2 8B; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2024-09-10 |
| Context window | 8k | 128k |
| Parameters | 8B | 550B (55B active) |
| Architecture | decoder only | decoder only |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2023-03 | - |
Pricing and availability
| Pricing attribute | Llama Guard 2 8B | Nemotron 3 Ultra |
|---|---|---|
| Input price | $0.05/1M tokens | - |
| Output price | $0.25/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Llama Guard 2 8B | Nemotron 3 Ultra |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | 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 is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
Pricing coverage is uneven: Llama Guard 2 8B has $0.05/1M input tokens and Nemotron 3 Ultra has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama Guard 2 8B when provider fit and broader provider choice are central to the workload. Choose Nemotron 3 Ultra 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. 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, Llama Guard 2 8B or Nemotron 3 Ultra?
Nemotron 3 Ultra supports 128k tokens, while Llama Guard 2 8B supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama Guard 2 8B or Nemotron 3 Ultra open source?
Llama Guard 2 8B is listed under Open Source. Nemotron 3 Ultra 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.
Where can I run Llama Guard 2 8B and Nemotron 3 Ultra?
Llama Guard 2 8B is available on Fireworks AI, OctoAI API (Deprecated), and Replicate API. Nemotron 3 Ultra is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama Guard 2 8B over Nemotron 3 Ultra?
Nemotron 3 Ultra fits 16x more tokens; pick it for long-context work and Llama Guard 2 8B for tighter calls. If your workload also depends on provider fit, start with Llama Guard 2 8B; if it depends on long-context analysis, run the same evaluation with Nemotron 3 Ultra.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.