Open-source engine for faster local language model inference with bit-for-bit identical output
Stage
Startup
Not given
Founded
2025
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Based in
CA
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Pricing model
Freemium
Open source
Pricing
Free: $0/month with 100 API calls/month, 1 seat, basic analytics, 30-day retention. Pro: $49/month with unlimited API calls, 5 seats, full analytics, hard spending caps, 90-day retention.
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Key features
Real-time cost tracking with per-model and per-tag breakdowns
Budget alerts via email, Slack, or Teams at configurable thresholds
Hard spending caps that block requests with 429 response
Rate limiting with sliding window per API key
Support for 9 LLM providers and 60+ models
Analytics dashboard with daily spend charts and latency metrics
Works with any programming language via HTTP proxy
AES-256 encryption for provider API keys with BYOK model
90-day data retention on Pro plan
Tag-based cost attribution by team, feature, or customer
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
Minimal 31ms proxy overhead, only 3.6% latency impact on typical calls
No SDKs required, works with any HTTP client out of the box
Never stores prompts or completions, only billing metadata
Hard spending caps enforced by Redis to prevent overspend
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