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Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
Chinese AGI company building multimodal LLMs, Hailuo video, speech and music models, plus AI apps and open APIs.
Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
No public pricing
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦On-demand GPU pods across 30+ GPU types and 31 regions
- ✦Serverless GPU endpoints with sub-200ms cold starts
- ✦Zero idle cost billing for inference workloads
- ✦Multi-node clusters for distributed training
- ✦Persistent network storage for full pipelines
- ✦Real-time logs, monitoring and autoscaling from 0 to hundreds of workers
- ✦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
- ✦Agent-first IDE experience
- ✦Autonomous planning and code execution
- ✦Integrated editor, terminal and browser control
- ✦Powered by Google's Gemini models
- ✦High-level developer supervision
- ✦Serverless GPU compute defined in Python
- ✦Sub-second container cold starts
- ✦Autoscale 0 to 1000+ GPUs
- ✦Inference, training and batch workloads
- ✦Secure sandboxes for untrusted code
- ✦Built-in logging and observability
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Renting GPUs for model training and fine-tuning
- →Deploying low-latency real-time inference APIs
- →Running AI agents that need to scale instantly
- →Processing compute-heavy batch or distributed workloads
- →Coding and agentic tasks
- →AI video generation
- →Text-to-speech and music creation
- →Building on MiniMax model APIs
- →Building apps with AI agents
- →Automating multi-step coding tasks
- →Prototyping and iterating on software
- →Assisting developers on complex work
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes