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 K2.5는 오픈 소스, 네이티브 Multimodal 에이전틱 Model로, Kimi-K2-Base 위에 약 15조 개의 혼합된 시각 및 Text token 을 지속적으로 사전 학습하여 구축되었습니다. 1T-파라미터 MoE 아키텍처(32B 활성)와 256K 컨텍스트 길이를 가지고 Vision과 언어 이해를 원활하게 통합하며, 고급 에이전틱 기능을 제공하여 인스턴트 및 사고 모드, 대화 및 에이전틱 패러다임을 모두 지원합니다....
Total Context:
262K
Max output:
262K
Input:
$
0.45
/ M Tokens
Input:
$
text
/ M Tokens
Output:
$
2.25
/ M Tokens
