Side-by-side comparison of LFM2.5-8B-A1B (Liquid AI) and MiMo-V2.5-Pro (Xiaomi (MiMo)) for self-hosted deployment of the open-weight model. LFM2.5-8B-A1B is rated conditional; MiMo-V2.5-Pro is conditional. They part ways on licence: LFM2.5-8B-A1B is "LFM Open License 1.0", MiMo-V2.5-Pro 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 Per the published LICENSE file, MiMo-V2.5-Pro ships under MIT, so the weights themselves carry no commercial restriction. The remaining EU-readiness gaps are the China-based vendor and the corpus disclosure that names training-stage categories (text pre-training, multimodal pre-training, SFT, RL, MOPD) without listing datasets — both should be addressed in any GPAI deployer file before regulated use. |
| 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 | — | 54/100 |
| Speed | — | 65 tok/s |
| Blended price | — | $1.50/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.