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Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
Developer platform for fast serverless inference and training of open generative models, billed per token or GPU-second.
GPU rental marketplace with per-second billing across thousands of GPUs, aimed at AI training, inference, and fine-tuning workloads.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- ✦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
- ✦Serverless per-token inference with OpenAI/Anthropic-compatible APIs
- ✦On-demand dedicated and reserved GPU deployments
- ✦Fine-tuning and reinforcement-learning training pipelines
- ✦Large library of open LLM, vision, image and audio models
- ✦Optimized inference engine for throughput and latency
- ✦On-demand GPU cloud with per-second billing
- ✦Interruptible instances at discounted rates for batch/fault-tolerant jobs
- ✦Reserved capacity with 1, 3, or 6-month terms for steady workloads
- ✦Serverless deployment with autoscale-to-zero for inference endpoints
- ✦Dedicated multi-node clusters with InfiniBand for large-scale training
- ✦Python SDK and CLI plus REST API for programmatic provisioning
- ✦Access to 68+ GPU types across 40+ data centers
- ✦Pre-configured templates for popular open-source models
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects
- →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
- →Serving open models in production apps and agents
- →Fine-tuning models on private data
- →Powering code assistants, chatbots and RAG at scale
- →ML engineers training or fine-tuning models on rented GPUs
- →Startups running inference at scale without owning hardware
- →Developers needing quick, low-cost access to specific GPU types
- →Teams building AI agents that autonomously provision compute