Side-by-side comparison of Ling-2.6 1T (inclusionAI · China) and Llama 4 Maverick (Meta · USA) for self-hosted deployment of the open-weight model. Ling-2.6 1T is rated conditional; Llama 4 Maverick is conditional. They part ways on licence: Ling-2.6 1T is "MIT", Llama 4 Maverick is "Llama community".
| 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 Llama 4 flagship: MoE with 17B active over 128 experts, natively multimodal (text + images). Same Llama community licence as the family: 700M MAU cap, acceptable-use policy, 'Built with Llama' attribution. |
| Last reviewed | 2026-05-03 | 2026-04-15 |
| Open-weight | ||
| Licence | MIT | Llama community |
| Commercial use | Unrestricted | With caps |
| Training data | Undisclosed | Undisclosed |
| Origin | China | USA |
| Performance & pricing? | ||
| Quality index | — | 18/100 |
| Speed | — | 116 tok/s |
| Blended price | — | $0.50/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.