Kimi-K2.5
Kimi K2.5 continues training from K2 Base on mixed visual and text data. It combines instant and thinking behavior within one checkpoint and adds a MoonViT vision encoder.
Visual input changes the coding workflow
The launch article demonstrates using images and video for interface generation and visual debugging. The training combines visual and text tokens rather than placing a separate image-captioning service in front of an unchanged K2 text model.Kimi K2.5 visual reasoning and agent training
Product modes do not create four model checkpoints
At launch, Kimi offered Instant, Thinking, Agent and Agent Swarm modes. The swarm system used a trained orchestrator with parallel workers. These product modes and their surrounding tools should not be counted as four independently released weight models.Kimi K2.5 visual reasoning and agent training
Use the K2.5 input format
The model card records corrections to its default system prompt and image-start token after release. A local application needs the matching multimodal processor and chat template.Kimi-K2.5 model card
The license requires Kimi K2.5 attribution for products above 100 million monthly users or US$20 million monthly revenue.Kimi K2.5 license
Specifications & access
| Detail | Value and conditions |
|---|---|
| Launch date | |
| Access | Downloadable |
| Model identifiers | moonshotai/Kimi-K2.5kimi-k2.5 |
| Context window | 262,144 tokens Published checkpoint limit; this is not a promise of continued API access. Kimi-K2.5 checkpoint configuration |
| Parameters | 1 trillion total; 32 billion active. The vision encoder is listed separately as 400 million parameters.Kimi-K2.5 model card |
| Training ancestry | Kimi-K2-Base, followed by approximately 15 trillion visual and text tokens.Kimi-K2.5 model card |
| Weight license | Modified MIT.Kimi K2.5 license |
| Former API | kimi-k2.5 is listed as deprecated; weights remain published.Kimi model catalog |
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