Side-by-side comparison of DeepSeek-V4-Pro (DeepSeek · China) and Step-3.7-Flash (StepFun) for self-hosted deployment of the open-weight model. DeepSeek-V4-Pro is rated conditional; Step-3.7-Flash is conditional. They part ways on licence: DeepSeek-V4-Pro is "MIT", Step-3.7-Flash 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. | Conditional Per the published Apache 2.0 LICENSE, the Step-3.7-Flash weights ship without commercial restriction — a 198B / 11B-active vision-language MoE with a 256k-token context aimed at tool-heavy and agentic workflows. The remaining EU-readiness gaps are the entirely undisclosed training corpus and StepFun's Shanghai-based vendor jurisdiction; deploy on self-managed EU infrastructure and document the Art. 50 transparency story for any synthetic or biometric output. |
| Last reviewed | 2026-04-28 | 2026-05-30 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Categories only | Undisclosed |
| Origin | China | China (Shanghai) |
| Performance & pricing? | ||
| Quality index | 52/100 | — |
| Speed | 36 tok/s | — |
| Blended price | $2.17/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.