Kimi K2 vs Llama Guard 3 1B
Kimi K2 (2025) and Llama Guard 3 1B (2024) are general-purpose language models from Moonshot AI and AI at Meta. Kimi K2 ships a 262K-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 $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama Guard 3 1B is ~400% cheaper at $0.1/1M; pay for Kimi K2 only for provider fit.
Specs
| Released | 2025-07-11 | 2024-09-25 |
| Context window | 262K | — |
| Parameters | 1K | 1B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Kimi K2 | Llama Guard 3 1B | |
|---|---|---|
| Input price | $0.5/1M tokens | $0.1/1M tokens |
| Output price | $2/1M tokens | $0.1/1M tokens |
| Providers |
Capabilities
| Kimi K2 | Llama 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 function calling: Kimi K2 and structured outputs: Kimi K2. 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, Kimi K2 lists $0.5/1M input and $2/1M 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 $0.85 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Kimi K2 when provider fit and broader provider choice 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, Kimi K2 or Llama Guard 3 1B?
Llama Guard 3 1B is cheaper on tracked token pricing. Kimi K2 costs $0.5/1M input and $2/1M 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 Kimi K2 or Llama Guard 3 1B open source?
Kimi K2 is listed under Proprietary. 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 function calling, Kimi K2 or Llama Guard 3 1B?
Kimi K2 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, Kimi K2 or Llama Guard 3 1B?
Kimi K2 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 Kimi K2 and Llama Guard 3 1B?
Kimi K2 is available on OpenRouter, AWS Bedrock, and GCP Vertex AI. Llama Guard 3 1B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Kimi K2 over Llama Guard 3 1B?
Llama Guard 3 1B is ~400% cheaper at $0.1/1M; pay for Kimi K2 only for provider fit. If your workload also depends on provider fit, start with Kimi K2; if it depends on provider fit, run the same evaluation with Llama Guard 3 1B.
Continue comparing
Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.