Llama Guard 2 8B vs ShieldGemma 9B
Llama Guard 2 8B (2024) and ShieldGemma 9B (2024) are compact production models from AI at Meta and Google DeepMind. Llama Guard 2 8B ships a 8K-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.
ShieldGemma 9B is safer overall; choose Llama Guard 2 8B when provider fit matters.
Specs
| Released | 2024-04-18 | 2024-07-01 |
| Context window | 8K | 8K |
| Parameters | 8B | 9B |
| Architecture | decoder only | decoder only |
| License | Open Source | 1 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama Guard 2 8B | ShieldGemma 9B | |
|---|---|---|
| Input price | $0.05/1M tokens | - |
| Output price | $0.25/1M tokens | - |
| Providers |
Capabilities
| Llama Guard 2 8B | ShieldGemma 9B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
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 ShieldGemma 9B has no token price sourced yet. Provider availability is 3 tracked routes versus 1. 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 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, Llama Guard 2 8B or ShieldGemma 9B?
Llama Guard 2 8B supports 8K 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 Llama Guard 2 8B or ShieldGemma 9B open source?
Llama Guard 2 8B is listed under Open Source. 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.
Where can I run Llama Guard 2 8B and ShieldGemma 9B?
Llama Guard 2 8B is available on Fireworks AI, OctoAI API, and Replicate API. ShieldGemma 9B is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama Guard 2 8B over ShieldGemma 9B?
ShieldGemma 9B is safer overall; choose Llama Guard 2 8B when provider fit matters. If your workload also depends on provider fit, start with Llama Guard 2 8B; if it depends on provider fit, run the same evaluation with ShieldGemma 9B.
Continue comparing
Last reviewed: 2026-04-15. Data sourced from public model cards and provider documentation.