GLM-5.1 vs Llama Guard 3 1B
GLM-5.1 (2026) and Llama Guard 3 1B (2024) are frontier reasoning models from Zhipu AI and AI at Meta. GLM-5.1 ships a 200k-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 $0.95/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama Guard 3 1B is ~850% cheaper at $0.1/1M; pay for GLM-5.1 only for coding workflow support.
Specs
| Released | 2026-03-27 | 2024-09-25 |
| Context window | 200k | — |
| Parameters | 744B total, 40-44B active | 1B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| GLM-5.1 | Llama Guard 3 1B | |
|---|---|---|
| Input price | $0.95/1M tokens | $0.1/1M tokens |
| Output price | $3.15/1M tokens | $0.1/1M tokens |
| Providers |
Capabilities
| GLM-5.1 | 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 reasoning mode: GLM-5.1, function calling: GLM-5.1, tool use: GLM-5.1, structured outputs: GLM-5.1, and code execution: GLM-5.1. 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, GLM-5.1 lists $0.95/1M input and $3.15/1M 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 $1.51 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.
Choose GLM-5.1 when coding workflow support 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, GLM-5.1 or Llama Guard 3 1B?
Llama Guard 3 1B is cheaper on tracked token pricing. GLM-5.1 costs $0.95/1M input and $3.15/1M 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 GLM-5.1 or Llama Guard 3 1B open source?
GLM-5.1 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 reasoning mode, GLM-5.1 or Llama Guard 3 1B?
GLM-5.1 has the clearer documented reasoning mode signal in this comparison. If reasoning mode 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, GLM-5.1 or Llama Guard 3 1B?
GLM-5.1 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 tool use, GLM-5.1 or Llama Guard 3 1B?
GLM-5.1 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GLM-5.1 and Llama Guard 3 1B?
GLM-5.1 is available on Z.ai and OpenRouter. 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: 2026-04-24. Data sourced from public model cards and provider documentation.