Side-by-side comparison of DeepSeek-V4-Pro (DeepSeek · China) and GLM-4.5 (Zhipu AI · China) for self-hosted deployment of the open-weight model. DeepSeek-V4-Pro is rated conditional; GLM-4.5 is conditional. They part ways on commercial use: DeepSeek-V4-Pro is "Unrestricted", GLM-4.5 is "Yes".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Per the published LICENSE file, DeepSeek-V4-Pro ships under MIT with no commercial restrictions, so the weights themselves are deployable. The caveats are non-EU jurisdiction and a training corpus described only by aggregate token count (32T+) without a dataset list — both should be documented in any GDPR or AI Act compliance file before regulated use. | Conditional MoE flagship from Zhipu under MIT. Strong agentic and coding benchmarks. Same Chinese-origin alignment and geopolitical considerations as DeepSeek / Qwen. |
| Last reviewed | 2026-04-28 | 2026-04-15 |
| Open-weight | ||
| Licence | MIT | MIT |
| Commercial use | Unrestricted | Yes |
| Training data | Categories only | Undisclosed |
| Origin | China | China |
| Performance & pricing? | ||
| Quality index | 52/100 | 26/100 |
| Speed | 36 tok/s | 44 tok/s |
| Blended price | $2.17/M | $0.84/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.