Llama Guard 4 12B vs Mixtral 8x22B Instruct v0.3
Llama Guard 4 12B (2025) and Mixtral 8x22B Instruct v0.3 (2024) are compact production models from AI at Meta and MistralAI. Llama Guard 4 12B ships a 164K-token context window, while Mixtral 8x22B Instruct v0.3 ships a 64K-token context window. On pricing, Llama Guard 4 12B costs $0.18/1M input tokens versus $2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama Guard 4 12B is ~1011% cheaper at $0.18/1M; pay for Mixtral 8x22B Instruct v0.3 only for provider fit.
Specs
| Released | 2025-04-05 | 2024-07-01 |
| Context window | 164K | 64K |
| Parameters | — | 8x22B |
| Architecture | decoder only | mixture of experts |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama Guard 4 12B | Mixtral 8x22B Instruct v0.3 | |
|---|---|---|
| Input price | $0.18/1M tokens | $2/1M tokens |
| Output price | $0.18/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Llama Guard 4 12B | Mixtral 8x22B Instruct v0.3 | |
|---|---|---|
| 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 function calling: Mixtral 8x22B Instruct v0.3 and structured outputs: Llama Guard 4 12B. 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 Guard 4 12B lists $0.18/1M input and $0.18/1M output tokens, while Mixtral 8x22B Instruct v0.3 lists $2/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama Guard 4 12B lower by about $1.82 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Llama Guard 4 12B when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Mixtral 8x22B Instruct v0.3 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.
FAQ
Which has a larger context window, Llama Guard 4 12B or Mixtral 8x22B Instruct v0.3?
Llama Guard 4 12B supports 164K tokens, while Mixtral 8x22B Instruct v0.3 supports 64K 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 4 12B or Mixtral 8x22B Instruct v0.3?
Llama Guard 4 12B is cheaper on tracked token pricing. Llama Guard 4 12B costs $0.18/1M input and $0.18/1M output tokens. Mixtral 8x22B Instruct v0.3 costs $2/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama Guard 4 12B or Mixtral 8x22B Instruct v0.3 open source?
Llama Guard 4 12B is listed under Open Source. Mixtral 8x22B Instruct v0.3 is listed under Apache 2.0. 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 function calling, Llama Guard 4 12B or Mixtral 8x22B Instruct v0.3?
Mixtral 8x22B Instruct v0.3 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.
Which is better for structured outputs, Llama Guard 4 12B or Mixtral 8x22B Instruct v0.3?
Llama Guard 4 12B 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 Llama Guard 4 12B and Mixtral 8x22B Instruct v0.3?
Llama Guard 4 12B is available on NVIDIA NIM, Replicate API, and OpenRouter. Mixtral 8x22B Instruct v0.3 is available on Replicate API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.