Side-by-side comparison of LFM2.5-8B-A1B (Liquid AI) and MiMo-V2.5 (Xiaomi (MiMo)) for self-hosted deployment of the open-weight model. LFM2.5-8B-A1B is rated conditional; MiMo-V2.5 is conditional. They part ways on licence: LFM2.5-8B-A1B is "LFM Open License 1.0", MiMo-V2.5 is "MIT".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Per the published LFM Open License v1.0, Liquid AI's terms are Apache-2.0-derived but cap free commercial use at USD 10M annual company revenue — above that threshold deployers must negotiate a paid licence with [email protected]. The model itself is a strong 8.3B / 1.5B-active MoE built for CPU and edge inference, but the 38-trillion-token training corpus is undisclosed and Liquid AI is a US-based MIT spinoff, so EU regulated buyers should run their own DPIA and document the data-transfer story alongside any commercial-tier negotiation. | Conditional MiMo-V2.5 is the omnimodal sibling of MiMo-V2.5-Pro — text, vision, audio, and video on a single sparse-MoE backbone, also under MIT. Same posture as the Pro: deployable weights, but the China origin and stage-level training disclosure mean any EU rollout needs self-hosting plus a deployer-prepared GPAI compliance file, with extra attention to Article 50 transparency for synthetic and biometric outputs. |
| Last reviewed | 2026-05-30 | 2026-04-28 |
| Open-weight | ||
| Licence | LFM Open License 1.0 | MIT |
| Commercial use | Free under $10M revenue | Unrestricted |
| Training data | Undisclosed | Categories only |
| Origin | USA (Boston) | China |
| Performance & pricing? | ||
| Quality index | — | 49/100 |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.