Pyyan / Compare / GLM-5.3-Flash vs MiMo-V2.6-Pro
GLM-5.3-Flash vs MiMo-V2.6-Pro
2 of 5Open-Weight Models · verified 29 Sept 2026
GLM-5.3-FlashZhipu AIcurrentXMiMo-V2.6-ProXiaomicurrent
| Specification | GLM-5.3-Flash | MiMo-V2.6-Pro |
|---|---|---|
| Summary | MIT licensed, a million tokens of context, fifteen cents a million in. | A trillion parameters under the MIT licence. |
| Context | 1M | 1M |
| Input ($/Mtok) | $0.15 | Weights only |
| Output ($/Mtok) | $0.5 | Weights only |
| Licence | MIT | MIT |
| Max output | 32K | Not published |
| Parameters | 320B total, 18B active | 1.02T total, 42B active |
| Released | 26 Aug 2026 | 21 Sep 2026 |
| Model ID | zai-org/GLM-5.3-Flash | XiaomiMiMo/MiMo-V2.6-Pro |
| Category | Open-Weight Models | Open-Weight Models |
| Official | — | Xiaomi ↗ |
Highlighted rows are where these differ.
GLM-5.3-Flash
- MIT licensed, which is about as permissive as an open release gets
- 320B total parameters, 18B active, with a 1M token context
- $0.15 in and $0.50 out per million tokens
Best for permissive licence at scale.
MiMo-V2.6-Pro
- 1.02T total parameters, 42B active per token, a 4.1% activation ratio
- Text, image, video and audio in, with a 1M token context
- Shipped with 7,000+ reinforcement learning environments and the framework that trained it
Best for multimodal work on your own cluster.