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Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Chinese AI lab DeepSeek offering free chat apps and low-cost API access to its frontier V-series and R-series reasoning models.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
Unified API and gateway routing requests across 200+ models from 40+ providers, with cost tracking and a free BYOK tier.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
No public pricing
Free trial available
No public pricing
Free trial available
- ✦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
- ✦Free DeepSeek chat (web and app)
- ✦Open API platform
- ✦V-series and R-series reasoning models
- ✦DeepSeek-V4 with long context and stronger agent ability
- ✦OpenAI/Anthropic-compatible API
- ✦Extensive published model lineup
- ✦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
- ✦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
- ✦Visual workflow studio for agents
- ✦RAG knowledge pipelines
- ✦Agent runtime with tools and memory
- ✦Marketplace of models and plugins
- ✦Publish as app, API or MCP tool
- ✦Logging, analytics and monitoring
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Free AI chat and assistance
- →Building apps via API
- →Reasoning and coding tasks
- →Low-cost LLM inference
- →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
- →Route across many LLM providers from one API
- →Track and control AI spend
- →Avoid vendor lock-in with provider switching
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale