LLM ReferenceLLM Reference

Llama 3.3 70B vs Llama Guard 3 1B

Llama 3.3 70B (2025) and Llama Guard 3 1B (2024) are compact production models from AI at Meta. Llama 3.3 70B ships a 8K-token context window, while Llama Guard 3 1B ships a not-yet-sourced context window. On pricing, Llama Guard 3 1B costs $0.1/1M input tokens versus $0.9/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama Guard 3 1B is ~800% cheaper at $0.1/1M; pay for Llama 3.3 70B only for vision-heavy evaluation.

Specs

Released2025-12-092024-09-25
Context window8K
Parameters70B1B
Architecturedecoder onlydecoder only
LicenseTrueOpen Source
Knowledge cutoff2024-12-

Pricing and availability

Llama 3.3 70BLlama Guard 3 1B
Input price$0.9/1M tokens$0.1/1M tokens
Output price$0.9/1M tokens$0.1/1M tokens
Providers

Capabilities

Llama 3.3 70BLlama Guard 3 1B
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 differs most on vision: Llama 3.3 70B, multimodal input: Llama 3.3 70B, function calling: Llama 3.3 70B, and tool use: Llama 3.3 70B. 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.

For cost, Llama 3.3 70B lists $0.9/1M input and $0.9/1M output tokens, while Llama Guard 3 1B lists $0.1/1M input and $0.1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama Guard 3 1B lower by about $0.8 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.

Choose Llama 3.3 70B when vision-heavy evaluation are central to the workload. Choose Llama Guard 3 1B when provider fit and lower input-token cost 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 is cheaper, Llama 3.3 70B or Llama Guard 3 1B?

Llama Guard 3 1B is cheaper on tracked token pricing. Llama 3.3 70B costs $0.9/1M input and $0.9/1M output tokens. Llama Guard 3 1B costs $0.1/1M input and $0.1/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Llama 3.3 70B or Llama Guard 3 1B open source?

Llama 3.3 70B is listed under True. Llama Guard 3 1B 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 vision, Llama 3.3 70B or Llama Guard 3 1B?

Llama 3.3 70B 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.

Which is better for multimodal input, Llama 3.3 70B or Llama Guard 3 1B?

Llama 3.3 70B 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, Llama 3.3 70B or Llama Guard 3 1B?

Llama 3.3 70B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Llama 3.3 70B and Llama Guard 3 1B?

Llama 3.3 70B is available on Fireworks AI. Llama Guard 3 1B is available on Fireworks 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: 2026-04-18. Data sourced from public model cards and provider documentation.