Side-by-side comparison of DeepSeek-V4-Pro (DeepSeek · China) and Gemma 4 (Google · USA) for self-hosted deployment of the open-weight model. DeepSeek-V4-Pro is rated conditional; Gemma 4 is EU-ready. They part ways on licence: DeepSeek-V4-Pro is "MIT", Gemma 4 is "Apache 2.0".
| 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. | EU-ready Major licence shift from Gemma 2/3: Apache 2.0 across the family. 140+ languages, multimodal (text/image/audio/video on small sizes), 128K-256K context. Strong permissive default for EU deployments that need robust multilingual support. |
| Last reviewed | 2026-04-28 | 2026-04-15 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Unrestricted | Yes |
| Training data | Categories only | Partial |
| Origin | China | USA |
| Performance & pricing? | ||
| Quality index | 52/100 | 32/100 |
| Speed | 36 tok/s | — |
| Blended price | $2.17/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.