Head to head
Xiaomi MiMo V2.6 Pro vs GLM-5.3
Which is better, Xiaomi MiMo V2.6 Pro or GLM-5.3?
Xiaomi MiMo V2.6 Pro finishes ahead of GLM-5.3 on the index, 89.4 to 87.9, and leads on all four scores: craft, speed, control and value. Both are scored on the same rubric, in the same week, and neither placing is sponsored.
Updated
Xiaomi MiMo V2.6 Pro
06 of 73
89.4
The strongest large open-weights model on the independent index, under MIT, for under a dollar out.
GLM-5.3
10 of 73
87.9
The same base as GLM-5.2, re-trained into one of the strongest open models available.
The four scores, side by side
| Score | Xiaomi MiMo V2.6 Pro | GLM-5.3 | Difference |
|---|---|---|---|
| Craft | 88 | 88 | — |
| Speed | 80 | 80 | — |
| Control | 93 | 90 | +3 |
| Value | 95 | 90 | +5 |
| Index score | 89.4 | 87.9 | +1.5 |
Which to pick
Xiaomi MiMo V2.6 Pro is the safer pick on every axis we score. GLM-5.3 earns its place in the index, but nothing in these four numbers argues for it over Xiaomi MiMo V2.6 Pro.
Xiaomi MiMo V2.6 Pro
MiMo V2.6 Pro replaced V2.5 Pro in September, and Xiaomi retires the old version on 21 October. It is a sparse model of about a trillion parameters with 42 billion active, it reads text, images, video and audio, and it leads the large open-weights models on the Artificial Analysis index. The weights are MIT-licensed and the hosted API costs 87 cents per million output tokens, a small fraction of any Western model at this level.
Where it shines
- Highest Artificial Analysis score of any large open-weights model
- MIT licence on a trillion-parameter model
- Reads text, images, video and audio natively
GLM-5.3
GLM-5.3 keeps GLM-5.2's base model and gets all of its gains from post-training, which lifted it into the top group of open models on both independent leaderboards. It takes a million tokens of context and is priced well below the Western flagships it now sits close to. The catch is the licence: unlike 5.2, it is published under Zhipu's own GLM-5.3 terms rather than MIT, so read them before you build a product on the weights.
Where it shines
- Among the top open models on both independent leaderboards
- Million-token context with 128,000 tokens of output
- Hosted API priced well below Western flagships