Side-by-side comparison of GLM-5.1 (Zhipu AI (Z.ai) · China) and Llama 3.1 8B Instruct (Meta Platforms · United States) for self-hosted deployment of the open-weight model. GLM-5.1 is rated conditional; Llama 3.1 8B Instruct is conditional. They part ways on licence: GLM-5.1 is "MIT", Llama 3.1 8B Instruct is "Llama 3.1 Community Licence".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Per current documentation, GLM-5.1 is released under a verbatim MIT License with no use restrictions, enabling self-hosted commercial deployment. However, training-data opacity, Beijing-based publisher, and Zhipu AI's presence on the US BIS Entity List create EU AI Act transparency and supply-chain screening risks for regulated deployers. | Conditional Per current documentation, Llama 3.1 8B Instruct is released under the Llama 3.1 Community Licence — a custom source-available licence rather than OSI open source. Commercial deployment is permitted below 700M MAU subject to the Acceptable Use Policy and attribution rules, but training-data opacity and US origin create EU AI Act transparency and data-transfer gaps that deployers should document. |
| Last reviewed | 2026-04-17 | 2026-04-17 |
| Open-weight | ||
| Licence | MIT | Llama 3.1 Community Licence |
| Commercial use | Unrestricted | Restricted (MAU cap + AUP) |
| Training data | Undisclosed | Token count only |
| Origin | China (Beijing) | United States |
| Performance & pricing? | ||
| Quality index | 44/100 | 12/100 |
| Speed | 48 tok/s | 160 tok/s |
| Blended price | $2.15/M | $0.10/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.