One OpenAI-compatible API and prepaid balance for nearly 500 AI models at lower prices
Open-source engine for faster local language model inference with bit-for-bit identical output
Stage
Not given
Not given
Founded
Not given
Not given
Based in
Not given
Not given
Pricing model
Freemium
Open source
Pricing
Free models with limited throughput; paid models charged per unit (language models per 1 million input and output tokens, images per image, video per second, speech per 1,000 characters, transcription per minute). Prices vary by model with discounts up to 50% compared to official rates. Example: Dee
Not given
Key features
Nearly 500 AI models from leading publishers
OpenAI-compatible and Anthropic-compatible API
Text, image, video, speech and transcription models
Per-key spending limits
MCP server integration with Codex, Claude Code, Cursor, Gemini CLI
Free models with limited throughput
Per-model pricing with no platform fee
Prepaid balance system
AI Workspace for team collaboration and research
Speculative decoding for faster token generation
Prompt caching for context reuse
Real-time prompt processing while typing
Concurrent request batching
Bit-for-bit identical output verification
Multi-GPU and multi-backend support (CUDA, Vulkan)
Vision model support with image encoding
Mixture-of-experts model support
RAD-1 automatic draft token generation
Cross-platform support for Windows and Linux
What makes it different
Single API key and balance for nearly 500 models with no platform fee
Discounts up to 50% compared to official model pricing
OpenAI and Anthropic API compatibility without changing request format
Works directly with Claude Code, Codex, Cursor and Gemini CLI via MCP server
No data used for model training
Exact deterministic inference: all default optimizations preserve bit-for-bit identical output compared to plain decoding
4.5× faster performance on editing tasks on small models compared to llama.cpp
Verifiable reproducibility through receipt system that records all request parameters
Nine optimization techniques enabled by default with ability to disable each individually
No dependency on draft models or external selections for speculative decoding