Side-by-side comparison of Kimi K2 Instruct (Moonshot AI · China) and Ling-2.6 1T (inclusionAI · China) for self-hosted deployment of the open-weight model. Kimi K2 Instruct is rated conditional; Ling-2.6 1T is conditional. They part ways on licence: Kimi K2 Instruct is "Modified MIT", Ling-2.6 1T is "MIT".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional 1T-parameter MoE (32B active) tuned for agentic and tool-use workflows. Modified MIT permits commercial use. Same Chinese-origin alignment and supply-chain considerations as DeepSeek and Qwen. | 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. |
| Last reviewed | 2026-04-16 | 2026-05-03 |
| Open-weight | ||
| Licence | Modified MIT | MIT |
| Commercial use | Yes | Unrestricted |
| Training data | Undisclosed | Undisclosed |
| Origin | China | China |
| Performance & pricing? | ||
| Quality index | 26/100 | — |
| Speed | 34 tok/s | — |
| Blended price | $1.04/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.