Side-by-side comparison of DeepSeek V3.2 (DeepSeek · China) and Ling-2.6 1T (inclusionAI · China) for self-hosted deployment of the open-weight model. DeepSeek V3.2 is rated conditional; Ling-2.6 1T is conditional. They part ways on commercial use: DeepSeek V3.2 is "Yes", Ling-2.6 1T is "Unrestricted".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional 685B successor to V3 with DeepSeek Sparse Attention for long context, scalable RL for agentic tasks. Vendor claims parity with GPT-5 (Speciale variant exceeds). MIT licence keeps weights clean; Chinese-origin considerations unchanged. | 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 | 2026-04-15 | 2026-05-03 |
| Open-weight | ||
| Licence | MIT | MIT |
| Commercial use | Yes | Unrestricted |
| Training data | Undisclosed | Undisclosed |
| Origin | China | China |
| Performance & pricing? | ||
| Quality index | 32/100 | — |
| Speed | 32 tok/s | — |
| Blended price | $0.32/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.