Side-by-side comparison of DeepSeek-V4-Pro (DeepSeek · China) and Laguna XS.2 (Poolside · USA) for self-hosted deployment of the open-weight model. DeepSeek-V4-Pro is rated conditional; Laguna XS.2 is conditional. They part ways on licence: DeepSeek-V4-Pro is "MIT", Laguna XS.2 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 model card, Laguna XS.2 is an Apache 2.0 33B / 3B-active MoE positioned for local agentic coding, with a 131k-token context and FP8 KV cache aimed at single-machine inference. Permissive license and self-hostable weights make EU-side deployment straightforward; the limits are vendor jurisdiction (San Francisco–headquartered, no published EU DPA for hosted endpoints) and a model card that does not describe the training corpus. |
| Last reviewed | 2026-04-28 | 2026-05-03 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Categories only | Undisclosed |
| Origin | China | USA |
| 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.