Side-by-side comparison of Codestral 22B (Mistral AI · France) and Ling-2.6 1T (inclusionAI · China) for self-hosted deployment of the open-weight model. Codestral 22B is rated conditional; Ling-2.6 1T is conditional. They part ways on licence: Codestral 22B is "MNPL (non-prod)", Ling-2.6 1T is "MIT".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional EU code model trained on 80+ languages. Licensed under Mistral Non-Production License — blocked for any production or commercial deployment without a paid commercial licence. Use Codestral Mamba (Apache 2.0) if you need commercial freedom. | 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 | MNPL (non-prod) | MIT |
| Commercial use | Paid licence req. | Unrestricted |
| Training data | Partial | Undisclosed |
| Origin | EU | China |
| Performance & pricing? | ||
| Quality index | — | — |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.