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Pay-per-use API hub aggregating 1000+ image, video, and audio generation models for developers building AI media pipelines.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Searchable directory of open-source AI agent 'skills' (SKILL.md files) for developers building with Claude, Codex, or ChatGPT agents.
Cloud platform from the makers of PyTorch Lightning for building, training and deploying AI in browser-based GPU Studios.
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
Free trial available
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Unified API access to 1000+ image/video/audio generation models
- ✦Pay-per-use pricing billed per image or per second of video
- ✦Includes chat/LLM model access (Claude, GPT, Gemini, etc.) priced per token
- ✦Account tiers unlock higher GPU limits and concurrency
- ✦CLI and desktop app for building workflows
- ✦Enterprise options with dedicated support and custom deployment
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Full-text search across millions of indexed SKILL.md files
- ✦Browse skills by creator or by occupation category
- ✦Inspect GitHub source links for each skill before use
- ✦REST API access to the skill catalog
- ✦One-click running of skills inside supported agent platforms
- ✦Browser-based Lightning Studios with on-demand GPUs
- ✦PyTorch Lightning training framework
- ✦Model training, fine-tuning and deployment
- ✦Collaborative, shareable ML environments
- ✦Scalable multi-GPU/multi-node compute
- ✦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
- →Integrating AI image/video generation into an app via API
- →Building automated content pipelines needing multiple AI models
- →Testing and comparing many generative models from one account
- →Scaling AI media production with volume-based account tiers
- →Accessing both media-generation and LLM APIs from one platform
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Finding an existing agent skill instead of writing one from scratch
- →Comparing similar skills across different creators
- →Building custom search or analytics on top of the skill catalog via API
- →Discovering skills relevant to a specific job function
- →Prototype and train ML models in the cloud
- →Fine-tune and deploy foundation models
- →Run reproducible AI experiments collaboratively
- →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