Kimi K2.6
kimi-k2.6Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and... Built by MoonshotAI.
Prices updated
Input price
$0.44
per 1M tokens · Standard
Output price
$2.45
per 1M tokens · Standard
Input limit
262K
tokens
Output limit
236K
tokens
Input formats
Output formats
Kimi K2.6 price history
5 price records since 9/25/2026 · 3 changes
Kimi K2.6 cost calculator
$21/month
Standard pricing
Overview
What is Kimi K2.6?
Kimi K2.6 is a text & reasoning and vision model from MoonshotAI. Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and... Its 262K context window and $0.44 input price make it a candidate for quality-focused production applications.
Benchmarks
Kimi K2.6 benchmarks & speed
How Kimi K2.6 scores on standardized evaluations, and where it lands among every model we track.
27.0
Intelligence Index
60tok/s
Output speed
1275
DesignArena Elo
Reasoning
GPQA Diamond
91.1%
Graduate-level scientific reasoning · top 21%
HLE
37.5%
Humanity's Last Exam · top 27%
Coding
SciCode
51.5%
Python for scientific computing · top 43%
Latency & design
- Time to first token
- 2.81s
- DesignArena win rate
- 54.8%
- Design battles judged
- 34,043
Independent scores from Artificial Analysis and DesignArena · updated 10/8/2026. Higher is better; ranks compare against every model we track with that score.
Rates
Kimi K2.6 pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.44
Per 1M tokens
Cached input · Standard
$0.12
Per 1M tokens
Capabilities
Kimi K2.6 Tools
Tools available when using Kimi K2.6 through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Supported
Deterministic seed
Supported
Parallel tool calls
Supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Measured results (AA Intelligence 27 · DesignArena Elo 1275) position it for demanding production work.
- 262K context supports large documents, repositories and extended conversations.
- Supports text & reasoning and vision workloads in one model.
Limitations
- Generated tokens cost 6× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
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