Side-by-side comparison of Laguna XS.2 (Poolside · USA) and MiniMax M2 (MiniMax · China) for self-hosted deployment of the open-weight model. Laguna XS.2 is rated conditional; MiniMax M2 is conditional. They part ways on licence: Laguna XS.2 is "Apache 2.0", MiniMax M2 is "Modified MIT".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | 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. | Conditional 229B agent-focused model from MiniMax, Modified MIT. Strong software-engineering and tool-use benchmarks. Family has iterated fast (M2 / M2.1 / M2.5 / M2.7 across 2025-2026). Same Chinese-origin alignment and supply-chain considerations as DeepSeek, Qwen, Kimi. |
| Last reviewed | 2026-05-03 | 2026-04-16 |
| Open-weight | ||
| Licence | Apache 2.0 | Modified MIT |
| Commercial use | Unrestricted | Yes |
| Training data | Undisclosed | Undisclosed |
| Origin | USA | China |
| Performance & pricing? | ||
| Quality index | — | 36/100 |
| Speed | — | 72 tok/s |
| Blended price | — | $0.53/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.