Kimik25
Kimi K2.5 is an open-weight, trillion-parameter multimodal model from Moonshot AI offering unified text, image, video and PDF understanding, a massive 256K context window, and coordinated agent-swarm capabilities for complex multi-step workflows at dramatically reduced inference cost.
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Quick Overview
Best for: AI Agents
What it does
AI Agents software for decision-makers comparing workflow fit and alternatives.
Best fit
AI Agents
Pricing snapshot
Freemium from Free (open-weight model — cost depends on your infra)
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Kimik25
Kimi K2.5 is Moonshot AI's open-source 1-trillion-parameter multimodal model designed to process text, images, videos and PDFs through a single unified architecture. Pre-trained on 15 trillion mixed visual and text tokens and built with a Mixture-of-Experts design, Kimi K2.5 activates only a small fraction of parameters per inference to deliver high intelligence with computational efficiency. It supports a 256K context window for long-form documents and conversations, native visual coding that generates production-ready UI from screenshots, and agent-swarm orchestration for parallelized tool use and multi-step workflows.
Kimi K2.5 targets developers, startups, researchers and enterprises that need open-weight flexibility, local deployment options for privacy/data sovereignty, and cost-effective inference for production multimodal and agentic applications.
Kimi K2.5 is an open-weight, trillion-parameter multimodal model from Moonshot AI offering unified text, image, video and PDF understanding, a massive 256K context window, and coordinated agent-swarm capabilities for complex multi-step workflows at dramatically reduced inference cost.
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Native Multimodal Processing
Unified model pre-trained on 15 trillion mixed visual and text tokens that handles text, images, videos and PDFs without switching between specialized models; can generate UI from screenshots and analyze video content.
1T Parameters with Mixture-of-Experts
Trillion-parameter Mixture-of-Experts architecture that activates ~32B parameters per inference (≈3.2% of total), enabling large capacity with computational efficiency.
256K Context Window
Extremely large context window that can process entire codebases or documents up to ~2 million characters, removing the need for complex retrieval-and-generation (RAG) pipelines.
Agent Swarm Intelligence
Coordinates up to 100 autonomous sub-agents executing up to 1,500 parallel tool calls and supports workflows with up to 300 sequential tool calls, with reported runtime reductions and stable instruction-following.
Visual Coding
Generates production-ready code (for example, React components) from UI screenshots or design mockups, including styling, state management, and accessibility considerations.
Open-Weight Accessibility & Local Deployment
Fully open-source weights with support for INT4 quantization to enable local inference on commodity hardware for privacy-sensitive use cases and data sovereignty.
Cost-Efficient Inference
Designed to be cost-efficient at approximately $0.39 per million input tokens; reported to be multiple times cheaper than comparable proprietary models.
OpenAI-Compatible API
Offers an OpenAI-compatible API format to enable drop-in replacement for existing integrations with minimal code changes.
Pricing
Kimi K2.5 is open-weight and can be self-hosted for free; actual free cloud-tier details are not provided.
Self-hosted (Open-source)
Free (open-weight model — cost depends on your infra)- Full model weights and ability to run locally
- INT4 quantization for lower-resource deployments
- No per-token cloud fees (infrastructure costs apply)
Cloud API (Moonshot / Kimi-backed)
Approximately $0.39 per million input tokens (as stated)- Managed inference with performance optimizations
- OpenAI-compatible API endpoints
- Scale without managing hardware
Enterprise
Not publicly listed- Custom SLAs, deployment assistance and enterprise integrations (contact for details)
Use Cases
End-to-End Visual-to-Code Generation
Convert UI screenshots or Figma designs into production-ready frontend components, accelerating UI development and design handoff.
Large-Scale Document and Legal Analysis
Analyze entire legal documents, contracts or large codebases without chunking thanks to the 256K context window, enabling deeper, coherent analysis across long inputs.
Autonomous Research & Automation
Deploy agent swarms to browse, analyze and synthesize information continuously, automate multi-step research tasks, and replace manual workflows with coordinated agents.
Multimodal Video and Image Understanding
Analyze video content and extract insights or summaries, process images and PDFs in the same pipeline as text, and build multimodal applications.
On-Premise/Privacy-Sensitive Deployments
Run INT4-quantized local inference to keep sensitive data on-premise while using the same model capabilities as cloud deployments.
Large-Scale Codebase Refactoring and Understanding
Perform multi-file refactors, understand project architecture, suggest consistent changes and update tests while maintaining context across the whole codebase.
Integrations
kimi-cli (GitHub)
Command-line tool to access Kimi K2.5 for local and cloud operations.
OpenAI-compatible API
Drop-in compatible API format to replace existing OpenAI integrations with minimal code changes.
INT4 Quantization Tooling
Quantization workflows to enable local, low-memory inference on commodity hardware for privacy-sensitive deployments.
Tooling & Agent Orchestration
Supports integration with external tools via agent sub-agents and parallel tool calls (up to reported limits).
Benefits
Limitations
Frequently Asked Questions
What exactly is Kimi K2.5 and how does it differ from previous Kimi models?
What makes Kimi K2.5's multimodal capabilities unique?
How does Kimi K2.5 achieve cost efficiency?
What is the agent swarm capability and what problems can it solve?
Can I run Kimi K2.5 locally and what are hardware requirements?
How does the 256K context window compare to other models?
How do I integrate Kimi K2.5 into existing applications?
Is Kimi K2.5 suitable for enterprise deployment and compliance?
Can I fine-tune Kimi K2.5 for specific domains?
Where can I get support or documentation?
Getting Started
- 1 Install Kimi CLI: Get the kimi-cli tool from GitHub and install it to access Kimi K2.5 from your terminal.
- 2 Configure Deployment: Choose cloud API access for maximum performance or set up local inference with INT4 quantization for privacy-sensitive workflows and configure your API key if using cloud.
- 3 Provide Multimodal Inputs: Use text, images, videos or PDFs as inputs to explore visual coding, video analysis, or long-document understanding.
- 4 Scale & Integrate: Use the OpenAI-compatible API format for drop-in replacement in existing apps and deploy agent swarms or production services leveraging the 256K context and agentic tool-call capabilities.
Support
General inquiries and support can be sent to [email protected].
Docs
Project documentation is referenced on the site; consult the documentation and GitHub repository for install guides and API references.
GitHub
Source code, the kimi-cli tool and installation instructions are available via the project's GitHub (link referenced on the page).
API
The page references an OpenAI-compatible API format and the project's documentation/GitHub for API usage details; no single documentation URL was provided on the page.
Not available
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