Kimi K2.6
by Moonshot · Released 2026
Moonshot AI's next-generation multimodal model. Designed for long-horizon coding, UI/UX generation from prompts and visual inputs, and multi-agent orchestration. Handles complex end-to-end coding tasks across Python, Rust, and Go.
Kimi K2.6
Powered by Moonshot · Mixture-of-Experts (next-gen multimodal)
Context Window
128K
Parameters
Undisclosed (MoE)
Max Output
16K
Category
LLM Chat
Overview
Kimi K2.6 is Moonshot AI's next-generation model, building on the K2.5 foundation with significant improvements in long-horizon coding, UI/UX generation, and multi-agent orchestration. It is designed to handle complex end-to-end software development tasks that span multiple files, languages, and architectural decisions.
The model excels at generating production-ready UI/UX from both text prompts and visual inputs — you can describe a design or provide a screenshot, and K2.6 will generate the corresponding React, Vue, or other framework code. It handles long-horizon coding tasks across Python, Rust, and Go, maintaining coherence and correctness across large codebases and multi-file changes.
K2.6's multi-agent orchestration capabilities enable complex workflows where multiple specialized agents collaborate on different aspects of a task — one agent handles frontend, another handles backend, a third manages testing, and K2.6 coordinates them all. This makes it particularly powerful for full-stack development, large refactoring projects, and automated software engineering pipelines.
Pricing
| Metric | Price |
|---|---|
| Input /1M tokens | ₹52.0000 |
| Output /1M tokens | ₹230.0000 |
1 credit = ₹1 = $0.01 USD. Prices shown from provider; CallMissed passes through with ~35% markup.
Key Highlights
- Long-horizon coding across Python, Rust, and Go
- UI/UX generation from prompts and visual inputs
- Multi-agent orchestration capabilities
- Production-ready interface generation
Benchmarks
| Benchmark | Score |
|---|---|
| SWE-bench | 79.1% |
| LiveCodeBench | 87.2% |
| HumanEval | 93.1% |
| UI Generation | SOTA |
Technical Details
- Next-generation MoE architecture building on K2.5 foundation
- Specialized for long-horizon coding across Python, Rust, and Go
- UI/UX generation from text prompts and visual inputs (screenshots, mockups)
- Multi-agent orchestration: coordinates specialized agents for complex tasks
- Improved code coherence across multi-file, multi-language projects
- Context window: 128K tokens
- Available via Moonshot API and CallMissed unified gateway
Strengths
- Specialized for long-horizon coding — maintains coherence across large projects
- UI/UX generation from both text and visual inputs is a unique capability
- Multi-agent orchestration for complex full-stack development workflows
- Strong multi-language support: Python, Rust, Go, and web frameworks
Limitations
- Newer model with limited production track record
- 128K context may be limiting for very large codebases
- UI generation quality may vary with complex or highly custom designs
Use Cases
API Example
curl https://api.callmissed.com/v1/chat/completions \
-H "Authorization: Bearer cm_YOUR_KEY" \
-d '{"model": "kimi-k2.6", "messages": [{"role": "user", "content": "Generate a production-ready login page in React"}]}'Endpoint: POST /v1/chat/completions · Model ID: kimi-k2.6