Side-by-side comparison of OLMo 2 32B (AllenAI · USA) and Qwen 3.5 (Alibaba · China) for self-hosted deployment of the open-weight model. OLMo 2 32B is rated EU-ready; Qwen 3.5 is conditional. They part ways on training data: OLMo 2 32B is "Disclosed", Qwen 3.5 is "Undisclosed".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | EU-ready Fully open model: weights, training data (Dolma 2), training code, checkpoints, and logs all published. Apache 2.0 across the board. Strongest choice when AI Act transparency obligations matter. | Conditional Hybrid Gated-DeltaNet + MoE flagship (397B total, 17B active) under Apache 2.0. Native vision, 201 languages, 262K context (1M with YaRN). Licence is clean; Chinese-origin alignment and supply-chain considerations persist. |
| Last reviewed | 2026-04-15 | 2026-04-15 |
| Open-weight | ||
| Licence | Apache 2.0 | Apache 2.0 |
| Commercial use | Yes | Yes |
| Training data | Disclosed | Undisclosed |
| Origin | USA | China |
| Performance & pricing? | ||
| Quality index | 11/100 | 40/100 |
| Speed | — | 53 tok/s |
| Blended price | — | $1.35/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.