Side-by-side comparison of Ling-2.6 1T (inclusionAI · China) and MiMo-V2.5 (Xiaomi (MiMo)) for self-hosted deployment of the open-weight model. Ling-2.6 1T is rated conditional; MiMo-V2.5 is conditional. They part ways on training data: Ling-2.6 1T is "Undisclosed", MiMo-V2.5 is "Categories only".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Per the published model card, Ling-2.6 1T is an MIT-licensed 1-trillion-parameter MoE with a 262k-token context, hybrid MLA + Linear attention and multi-token-prediction support, targeted at production agentic workloads. Permissive weights enable EU self-hosting in principle, though the deployment footprint is non-trivial; vendor jurisdiction (Ant Group, China) and undisclosed training data remain the regulated-buyer blockers. | 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 | 2026-05-03 | 2026-04-28 |
| Open-weight | ||
| Licence | MIT | MIT |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Undisclosed | Categories only |
| Origin | China | China |
| Performance & pricing? | ||
| Quality index | — | 49/100 |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.