Side-by-side comparison of Gemma 4 26B A4B Instruct (Google DeepMind · United States) and Ling-2.6 1T (inclusionAI · China) for self-hosted deployment of the open-weight model. Gemma 4 26B A4B Instruct is rated conditional; Ling-2.6 1T is conditional. They part ways on licence: Gemma 4 26B A4B Instruct is "Apache 2.0", Ling-2.6 1T is "MIT".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Based on published licence terms, Gemma 4 26B A4B ships under pure Apache 2.0 with no prohibited-use carve-outs — a departure from prior Gemma generations. The sparse-MoE architecture (25.2B total / 3.8B active) puts it in an ambiguous zone for EU AI Act GPAI systemic-risk classification, and US origin plus image-input support add transparency obligations that deployers should document. | 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 | 2026-04-17 | 2026-05-03 |
| Open-weight | ||
| Licence | Apache 2.0 | MIT |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Domain-level summary | Undisclosed |
| Origin | United States | China |
| Performance & pricing? | ||
| Quality index | 27/100 | — |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.