Side-by-side comparison of Ling-2.6 1T (inclusionAI · China) and MiniCPM5-1B (OpenBMB) for self-hosted deployment of the open-weight model. Ling-2.6 1T is rated conditional; MiniCPM5-1B is conditional. They part ways on licence: Ling-2.6 1T is "MIT", MiniCPM5-1B is "Apache 2.0".
| 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 Per the published Apache 2.0 LICENSE, the 1.08B-parameter weights carry no use restrictions and are well suited to on-device or edge deployments. Unusually for a Chinese-origin release, OpenBMB ships a full data card naming every pre-training and SFT corpus, which closes the AI Act Art. 53 transparency gap most peers leave open. The remaining hedge for regulated EU buyers is vendor jurisdiction (Tsinghua-affiliated lab, mainland China) — self-host the weights and treat any vendor-side service as out of scope. |
| Last reviewed | 2026-05-03 | 2026-05-30 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Undisclosed | Documented |
| Origin | China | China |
| Performance & pricing? | ||
| Quality index | 34/100 | — |
| Speed | — | — |
| Blended price | $0.85/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.