Side-by-side comparison of GLM-4.5 (Zhipu AI · China) and Mixtral 8x22B Instruct (Mistral AI · France) for self-hosted deployment of the open-weight model. GLM-4.5 is rated conditional; Mixtral 8x22B Instruct is EU-ready. They part ways on licence: GLM-4.5 is "MIT", Mixtral 8x22B Instruct is "Apache 2.0".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional MoE flagship from Zhipu under MIT. Strong agentic and coding benchmarks. Same Chinese-origin alignment and geopolitical considerations as DeepSeek / Qwen. | EU-ready A rare combination of permissive licensing, EU provenance, and credible multilingual coverage — Apache 2.0 leaves commercial deployment essentially unconstrained, and Paris-based Mistral simplifies the GDPR controller story compared with US-hosted peers. The catch is the training corpus: Mistral has never published a meaningful dataset breakdown, so AI Act transparency obligations on training-data summaries land squarely on the deployer. |
| Last reviewed | 2026-04-15 | 2026-05-19 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Yes | Unrestricted |
| Training data | Undisclosed | Undisclosed |
| Origin | China | EU (France) |
| Performance & pricing? | ||
| Quality index | 26/100 | — |
| Speed | 44 tok/s | — |
| Blended price | $0.84/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.