Kimi K2 Thinking
kimi-k2-thinkingKimi K2 Thinking is Moonshot AI's most advanced open reasoning model, built on a trillion-parameter MoE with 32B active parameters and a 256K context window. It's optimized for long-horizon, step-by-step reasoning with dynamic tool use, enabling sustained autonomous research, coding, and writing over hundreds of turns. It sets new open-source records on benchmarks like HLE and LiveCodeBench, and maintains stable multi-agent, tool-heavy workflows (200–300 calls) while balancing deep reasoning with efficient inference.
- Context
- 262.1K tokens
- Endpoint
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Pricing
Quick Start
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from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="kimi-k2-thinking", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="kimi-k2-thinking",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )Supported Parameters
API docsmodelmessagesmax_tokenstemperaturetop_pstreamtoolsreasoning_effortstream_optionsthinkingextra_bodyCursor IDE Model IDs
Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
Compare with Other Models
See how this model compares to others from the same provider.
Kimi K2.7 Code
Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, designed for long-horizon software engineering and agentic development workflows. Built on a native multimodal Mixture-of-Experts (MoE) architecture, it supports text, image, and video inputs and operates exclusively in thinking mode, preserving reasoning across multi-turn interactions. With approximately 1T total parameters and 32B activated per token, plus a 256K-token context window, K2.7 Code excels at end-to-end programming tasks, agentic task decomposition, repository-scale reasoning, and extended coding conversations, making it well suited for advanced coding agents and long-context development workflows.
- Context
- 262K
- Input
- $0.6712/M
- Output
- $3.35/M
Kimi K2 0905
Kimi K2-Instruct-0905 is the newest and strongest Kimi K2 model — a trillion-parameter MoE system with 32B active parameters. It delivers major gains in agentic coding, better frontend development results, and an expanded 256K context window for longer tasks.
- Context
- 262K
- Input
- $0.60/M
- Output
- $2.50/M
Kimi K2.6
Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, UI/UX generation, and multi-agent orchestration. It handles complex end-to-end development tasks across languages such as Python, Rust, and Go, and can transform prompts and visual inputs into production-ready interfaces. Powered by a scalable agent swarm architecture, K2.6 can coordinate hundreds of parallel sub-agents for autonomous task decomposition, enabling the generation of documents, websites, and spreadsheets in a single run without human intervention.
- Context
- 262.1K
- Input
- $0.60/M
- Output
- $2.80/M
Kimi K2.5
Kimi K2.5 is Moonshot AI's native multimodal model, designed to deliver state-of-the-art visual coding capabilities and support a self-directed agent swarm paradigm. Built upon Kimi K2 and further enhanced through continued pretraining on approximately 15 trillion mixed visual and text tokens, it achieves strong, well-balanced performance across general reasoning, visual understanding and coding, and agentic tool-calling workflows. With its robust multimodal foundations and agent-oriented design, Kimi K2.5 is well suited for advanced applications that combine vision, code, and autonomous agent collaboration.
- Context
- 262.1K
- Input
- $0.40/M
- Output
- $2.24/M