Pyyan / Compare / GLM-5.3 vs MiMo-V2.6-Pro
GLM-5.3 vs MiMo-V2.6-Pro
2 of 5Open-Weight Models · verified 29 Sept 2026
GLM-5.3Zhipu AIcurrentXMiMo-V2.6-ProXiaomicurrent
| Specification | GLM-5.3 | MiMo-V2.6-Pro |
|---|---|---|
| Summary | Post-trained from the GLM-5.2 base, with the weights following two weeks later. | A trillion parameters under the MIT licence. |
| Context | 1M | 1M |
| Input ($/Mtok) | $1.4 | Weights only |
| Output ($/Mtok) | $4.4 | Weights only |
| Licence | Open weights | MIT |
| Max output | 32K | Not published |
| Parameters | Not published | 1.02T total, 42B active |
| Released | 14 Aug 2026, weights 27 Aug | 21 Sep 2026 |
| Model ID | zai-org/GLM-5.3 | XiaomiMiMo/MiMo-V2.6-Pro |
| Category | Open-Weight Models | Open-Weight Models |
| Official | — | Xiaomi ↗ |
Highlighted rows are where these differ.
GLM-5.3
- Post-trained from the GLM-5.2 base rather than trained from scratch
- $1.40 in and $4.40 out per million tokens, with a 1M token window
- Announced 14 August, weights published 27 August
Best for the full-size open flagship.
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.