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Llama Guard 7B vs Llama 3.1 405B Instruct

Llama Guard 7B (2023) and Llama 3.1 405B Instruct (2024) are compact production models from AI at Meta. Llama Guard 7B ships a 2K-token context window, while Llama 3.1 405B Instruct ships a 128K-token context window. On pricing, Llama Guard 7B costs $0.2/1M input tokens versus $2.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama Guard 7B is ~1100% cheaper at $0.2/1M; pay for Llama 3.1 405B Instruct only for long-context analysis.

Specs

Released2023-12-072024-07-23
Context window2K128K
Parameters7B405B
Architecturedecoder onlydecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff--

Pricing and availability

Llama Guard 7BLlama 3.1 405B Instruct
Input price$0.2/1M tokens$2.4/1M tokens
Output price$0.2/1M tokens$2.4/1M tokens
Providers

Capabilities

Llama Guard 7BLlama 3.1 405B Instruct
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 structured outputs. 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.

For cost, Llama Guard 7B lists $0.2/1M input and $0.2/1M output tokens, while Llama 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama Guard 7B lower by about $2.2 per million blended tokens. Availability is 3 providers versus 11, so concentration risk also matters.

Choose Llama Guard 7B when provider fit and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct when long-context analysis, larger context windows, and broader provider choice 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.

FAQ

Which has a larger context window, Llama Guard 7B or Llama 3.1 405B Instruct?

Llama 3.1 405B Instruct supports 128K tokens, while Llama Guard 7B supports 2K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Llama Guard 7B or Llama 3.1 405B Instruct?

Llama Guard 7B is cheaper on tracked token pricing. Llama Guard 7B costs $0.2/1M input and $0.2/1M output tokens. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Llama Guard 7B or Llama 3.1 405B Instruct open source?

Llama Guard 7B is listed under Open Source. Llama 3.1 405B Instruct is listed under Open Source. 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, Llama Guard 7B or Llama 3.1 405B Instruct?

Both Llama Guard 7B and Llama 3.1 405B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Llama Guard 7B and Llama 3.1 405B Instruct?

Llama Guard 7B is available on Cloudflare Workers AI, Together AI, and Fireworks AI. Llama 3.1 405B Instruct is available on OctoAI API, Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Llama Guard 7B over Llama 3.1 405B Instruct?

Llama Guard 7B is ~1100% cheaper at $0.2/1M; pay for Llama 3.1 405B Instruct only for long-context analysis. If your workload also depends on provider fit, start with Llama Guard 7B; if it depends on long-context analysis, run the same evaluation with Llama 3.1 405B Instruct.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.