Kimi
Released April 20, 2026

Kimi K2.6

Kimi K2.6 by Moonshot AI is a 1T/32B-active native multimodal MoE model with MoonViT vision encoder, Agent Swarm (300 sub-agents), and 256K context.

Inputs
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Image
Outputs
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Model Overview

Capabilities, design details, and architectural traits

Kimi K2.6 - Native Multimodal Agentic MoE with Swarm Orchestration

Kimi K2.6 is Moonshot AI's open-source native multimodal agentic model. It advances practical capabilities across long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration - all within a single architecture handling text, images, and video without separate vision modules.

Key Capabilities

  • Long-Horizon Coding: Generalizes across Rust, Go, and Python spanning front-end, DevOps, and performance optimization; officially documented 12+ hour autonomous coding sessions with 4,000+ tool calls
  • Coding-Driven Design: Transforms prompts and visual inputs into production-ready interfaces with structured layouts, interactive elements, and animations
  • Agent Swarm: Scales to 300 domain-specialized sub-agents executing 4,000 coordinated steps in a single autonomous run - up from 100 sub-agents and 1,500 steps in K2.5; decomposes tasks into parallel subtasks delivering end-to-end outputs across documents, websites, and spreadsheets
  • Proactive Orchestration: Powers persistent 24/7 background agents managing schedules, executing code, and orchestrating cross-platform operations without human oversight

Reasoning Workflow

Supports Thinking and Instant modes. Thinking is interleaved between tool calls. Official documentation specifies preserved thinking as the recommended pattern: reasoning content from prior assistant turns is kept in message history across multi-turn interactions.

Benchmark Performance

Independent evaluations · Artificial Analysis

27.0%
Intelligence
61.8%
Coding Index
20.5%
Agentic Index

Accuracy & Capability Details

GPQA - Graduate Science91.1%
Humanity's Last Exam37.5%
SciCode - Scientific Coding51.5%
Instruction Following76.0%
Long Context Reasoning81.0%
τ²-Bench - Agentic Tasks95.9%
TerminalBench - System Control43.9%

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Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderKimiAnthropicAnthropic
Release DateApril 20, 2026September 22, 2026September 28, 2026
Knowledge Cutoff--Jun 2026
Context & Limits
Context Window262K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$0.95
Best Input Pricing
$4$2
Output Pricing
$4
Best Output Pricing
$20$10
Modalities
Inputs
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Outputs
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Benchmarks (0-100)
Intelligence Index27.0
57.6
Best Intelligence Index
56.0
Coding Index61.8--
Agentic Index20.5--
Kimi K2.6
Claude Opus 5.5
Claude Sonnet 5.5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

38%
Kimi K2.6
Humanity's Last Exam
Score: 38%
Kimi K2.6
61%
Claude Opus 5.5
Humanity's Last Exam
Score: 61%
Claude Opus 5.5
55%
Claude Sonnet 5.5
Humanity's Last Exam
Score: 55%
Claude Sonnet 5.5

Long Context Reasoning

Logical reasoning over long context windows.

81%
Kimi K2.6
Long Context Reasoning
Score: 81%
Kimi K2.6
85%
Claude Opus 5.5
Long Context Reasoning
Score: 85%
Claude Opus 5.5
83%
Claude Sonnet 5.5
Long Context Reasoning
Score: 83%
Claude Sonnet 5.5

SciCode Benchmark

Scientific coding and mathematical modeling.

52%
Kimi K2.6
SciCode Benchmark
Score: 52%
Kimi K2.6
67%
Claude Opus 5.5
SciCode Benchmark
Score: 67%
Claude Opus 5.5
61%
Claude Sonnet 5.5
SciCode Benchmark
Score: 61%
Claude Sonnet 5.5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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