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Kimi K2.6
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Moonshot AIMoonshot AIKimiReleased April 20, 2026

Kimi K2.6

256K context$0.745/M input$4.66/M output

Kimi K2.6 is Moonshot AI's multimodal model designed for complex coding tasks, coding-driven UI/UX generation, and multi-agent orchestration. It supports Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture enables autonomous task decomposition, scaling to hundreds of parallel sub-agents for efficient delivery of documents, websites, and spreadsheets without human oversight.

What is Kimi K2.6?

Kimi K2.6 is an AI model from Moonshot AI that Agent Mag tracks for pricing, context window, modalities, benchmarks, and API compatibility. Builders can use this page to compare Kimi K2.6 against other models for agent workflows and production deployments.

Model ID

Kimi K2.6 is Moonshot AI's multimodal model designed for complex coding tasks, coding-driven UI/UX generation, and multi-agent orchestration. It supports Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture enables autonomous task decomposition, scaling to hundreds of parallel sub-agents for efficient delivery of documents, websites, and spreadsheets without human oversight.

Architecture & Specifications
Architecture
Agent swarm architecture
Tokenizer
Other
Released
April 20, 2026
Modalities
Input
textimage
Output
text
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_pparallel_tool_callspresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Strengths
  • Handles complex end-to-end coding tasks across multiple programming languages
  • Supports coding-driven UI/UX generation
  • Autonomous multi-agent orchestration for task decomposition
  • Scales to hundreds of parallel sub-agents
  • Delivers production-ready outputs without human oversight
Limitations
  • High structured output error rate (6.19% for Moonshot AI)
  • Limited accuracy in knowledge-based tasks (32.8% AA-Omniscience Accuracy)
  • High hallucination rate in knowledge responses (60.7%)
  • Low performance in research-level physics reasoning (8.0% CritPt)
  • Relatively high latency compared to other providers
Recommended Use Cases
Long-horizon coding tasks
Coding-driven UI/UX generation
Autonomous document creation
Website and spreadsheet generation
Multi-agent orchestration for complex workflows

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Data enriched Apr 24, 2026. Pricing from OpenRouter API.