Moonshot AI
Text Generation
Kimi-K2.7-Code
Kimi K2.7 Code is a coding-focused agentic model built upon Kimi K2.6. With substantial improvements on real-world long-horizon coding tasks, it strengthens end-to-end task completion across complex software engineering workflows while improving token efficiency, reducing thinking-token usage by approximately 30% compared with Kimi K2.6....
Total Context:
262K
Max output:
262K
Input：
$
0.94
/ M Tokens
Input：
$
text
/ M Tokens
Output:
$
4.0
/ M Tokens
Moonshot AI
Text Generation
Kimi-K2.6
Kimi K2.6 is an open-source, native multimodal agentic model by Moonshot AI, achieving open-source state-of-the-art on benchmarks including HLE with tools, SWE-Bench Pro, and BrowseComp. Built on a MoE architecture with 1T total parameters and 32B activated, the model supports a 256K-token context window and multimodal inputs (image and video) via its MoonViT vision encoder. K2.6 is optimized for agentic workloads: it sustains 4,000+ tool calls over 12+ hours of continuous execution, scales to 300 parallel sub-agents × 4,000 steps per run to produce 100+ files from a single prompt, and supports both Thinking and Instant inference modes with function calling and multi-turn Preserve Thinking...
Total Context:
262K
Max output:
262K
Input：
$
0.77
/ M Tokens
Input：
$
text
/ M Tokens
Output:
$
4.0
/ M Tokens
Moonshot AI
Text Generation
Kimi-K2.5
Kimi K2.5は、Kimi-K2-Baseの上に約15兆の混合視覚およびText tokensで継続的に事前学習されたオープンソースのネイティブMultimodalなエージェントモデルです。1TパラメータMoEアーキテクチャ（32Bアクティブ）と256Kコンテキスト長を備え、Visionと言語の理解を高度なエージェント機能とシームレスに統合し、即時モードと思考モード、そして会話およびエージェントのパラダイムをサポートします。...
Total Context:
262K
Max output:
262K
Input：
$
0.45
/ M Tokens
Input：
$
text
/ M Tokens
Output:
$
2.25
/ M Tokens
