Affordable AI API gateway for frontier models at up to 89% below official pricing
Open-source engine for faster local language model inference with bit-for-bit identical output
Stage
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Founded
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Based in
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Pricing model
Paid
Open source
Pricing
Pay per million tokens in USD with no subscription or minimum spend. Prices vary by model and provider. Example flagship models: Claude (from $5.9/$29.5 input/output per million tokens), GPT-6-Astra (from $0.175/$0.875), Claude Opus (from $0.0125/$0.0625). Prompt caching at 10% of input rate where s
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Key features
OpenAI-compatible endpoint
Access to 171 frontier models
Automatic failover across upstream providers
Per-token billing from upstream usage reports
Full SSE streaming passthrough
Per-key rate limits and model allowlists
Complete usage logs with cost breakdown
Anthropic Messages API support
Prompt caching at 10% of input rate
Health tracking per provider family
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 for 171 models across 19 families with no per-provider signups
Up to 89% savings below official pricing on frontier models
Automatic failover ensures requests route around capacity outages
Pay only for tokens consumed with no monthly subscription or minimum spend
Exact billing metered from upstream usage, never estimated from characters
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