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Chinese AGI company building multimodal LLMs, Hailuo video, speech and music models, plus AI apps and open APIs.
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
Kimi is Moonshot AI's conversational assistant known for long-context chat, coding help, and agentic tasks.
Unified API and gateway routing requests across 200+ models from 40+ providers, with cost tracking and a free BYOK tier.
Free trial available
Free trial available
No public pricing
Free trial available
- ✦MiniMax M-series LLMs (M3, 1M context, MSA)
- ✦Hailuo AI video generation
- ✦Speech and music generation models
- ✦MiniMax Code agentic coding tool
- ✦Consumer apps (Hailuo, Xingye)
- ✦Open API and Token Plan for developers
- ✦One-line API calls to run community and proprietary AI models
- ✦Support for image, video, speech, and LLM generation models
- ✦Fine-tuning and custom model deployment via Cog
- ✦Per-second usage billing on shared or dedicated hardware
- ✦Automatic scaling for high-traffic private models
- ✦Thousands of community-published models with production APIs
- ✦Switch across 300+ hosted and local AI models
- ✦Native macOS app with global shortcut and screenshot-to-answer
- ✦Reusable agents, projects, and forked chats
- ✦Multimodal analysis of PDFs, images, and code
- ✦MCP tools and code execution
- ✦Local chat storage with encryptable API keys
- ✦Conversational AI assistant
- ✦Long-context document understanding
- ✦Coding assistance
- ✦Agent and plugin capabilities
- ✦Web and mobile app access
- ✦One API for 200+ models across 40+ providers
- ✦Provider switching without code changes
- ✦Real-time cost tracking
- ✦Bring-your-own-keys, free forever
- ✦Observability and guardrails
- ✦SOC 2 Type II certified
- →Coding and agentic tasks
- →AI video generation
- →Text-to-speech and music creation
- →Building on MiniMax model APIs
- →Developers embedding image/video/speech generation into an app via API
- →Teams deploying and scaling their own fine-tuned models
- →Builders comparing outputs from multiple AI models in one playground
- →Companies avoiding GPU infrastructure management for ML inference
- →Using multiple AI providers in one place
- →Explaining or fixing on-screen content instantly
- →Building reusable task-specific agents
- →Analyzing documents and screenshots privately
- →Answering questions and research
- →Summarizing long documents
- →Writing and editing help
- →Coding support
- →Route across many LLM providers from one API
- →Track and control AI spend
- →Avoid vendor lock-in with provider switching