Scale Ray AI workloads across thousands of GPUs on a managed platform.
Best for: Foundation model builders scaling multimodal data curation and distributed training, AI teams running batch embedding generation for search or retrieval
Flat $9.99/month subscription for curated open-weight coding models in Cline
Best for: Developers using Cline who want simplified model access with predictable pricing, Teams needing consistent, high-quota inference without managing multiple API keys
Distributed LLM inference across any GPUs – run bigger models without buying bigger hardware.
Best for: Homelab enthusiasts pooling GPU resources across multiple machines, Developers running agentic workflows with local LLMs and OpenAI-compatible APIs
High-performance open-source inference serving for LLMs and multimodal models.
Best for: Developers deploying LLMs in production with high throughput requirements, ML engineers optimizing inference latency on diverse hardware (NVIDIA, AMD, TPU)
Self-hosted AI model registry for enterprise inference, replacing Hugging Face
Best for: SREs managing large-scale model inference pipelines with vLLM or SGLang, Algorithm engineers needing fast, reliable model distribution across GPU clusters
Agent-native post-training to fine-tune small models in hours, fixed-price per run.
Best for: Developers fine-tuning small models on proprietary data for classification, extraction, routing, or reranking, Teams wanting full ownership of model weights without vendor lock-in
Unified platform for 200+ model APIs, GPU instances, and agent sandboxes.
Best for: Developers building AI-powered apps with multiple models via a single API, AI agent developers needing secure, isolated sandboxes for code execution and tool use
Ultra-fast pay-per-use AI media generation API with 1000+ models
Best for: Developers building media generation apps needing sub-second latency and a single API to 1000+ models, Content creators using the web or desktop app for fast image/video generation
Wafer Pass: Flat-rate coding agent inference on fastest open LLMs
Best for: Developers using agentic coding harnesses like OpenClaw, Claude Code, or Cline who want flat-rate pricing, Teams needing the fastest open-source LLM inference for GLM, Qwen, DeepSeek, or Kimi models
Self-improving inference API that routes tasks to the best model and learns from production traffic
Best for: Developers shipping production AI without managing infrastructure, Teams needing model improvement from live data without writing fine-tuning code
Open-source SDKs and hand-written kernels for on-device AI on Apple Silicon and Qualcomm NPUs.
Best for: Mobile app developers needing low-latency on-device LLM, voice, or vision, Edge AI engineers deploying to Apple Silicon or Qualcomm NPU hardware
