Head to head
GLM-5.3 vs Kimi K3
Which is better, GLM-5.3 or Kimi K3?
GLM-5.3 finishes ahead of Kimi K3 on the index, 87.9 to 85.1, 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
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.
Kimi K3
20 of 73
85.1
One of the strongest open-weights models, and it reads a million tokens without blinking.
The four scores, side by side
| Score | GLM-5.3 | Kimi K3 | Difference |
|---|---|---|---|
| Craft | 88 | 88 | — |
| Speed | 80 | 74 | +6 |
| Control | 90 | 91 | +1 |
| Value | 90 | 78 | +12 |
| Index score | 87.9 | 85.1 | +2.8 |
Which to pick
GLM-5.3 is the safer pick on every axis we score. Kimi K3 earns its place in the index, but nothing in these four numbers argues for it over GLM-5.3.
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
Kimi K3
Moonshot published K3 at a very large scale, with native vision, an explicit thinking mode and a million-token window, and in October it still ranks among the top open models on both independent leaderboards. Two caveats matter: the licence restricts commercial use above a revenue threshold, so it is open weights rather than open source, and the hosted API costs three dollars in and fifteen out, priced like a Western frontier model rather than a Chinese one.
Where it shines
- Million-token context handled properly rather than nominally
- Native vision and an explicit thinking mode
- Among the highest human-preference ratings of any open model