Liquid AI launches RIPL inference engine for faster responses
MarkTechPost: Liquid AI Launches RIPL, a Real-Time Inference Engine for Sub-50 ms LFMs
Liquid AI just announced Liquid RIPL, short for Real-time Inference Pipeline. RIPL is a low-latency engine that serves Liquid Foundation Models (LFMs) inside a live request path. It returns complete generated responses end-to-end in under 50 ms. It also claims that latency holds while traffic arrives continuously at peak load. For developers, the message is simple. Swap gradient-boosted trees for a generative model, and keep the latency budget. TL;DR Engine: Serves LFM2.5 models from 230
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Liquid AI launched RIPL, a real-time inference engine that serves language foundation models and returns complete responses in under 50 milliseconds. Most AI serving systems are designed for large batches and longer processing times, but applications like search ranking, fraud checks, and payment authorization require millisecond-speed answers, creating demand for faster inference. According to Liquid AI's benchmarks, RIPL achieves 5.6 to 28.4 times lower latency compared to vLLM when serving similar-sized models, with performance holding steady during continuous peak traffic. The engine is currently enterprise-only and has been deployed in production by at least one major company for latency-sensitive workloads.
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