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Markdown edition

# Liquid RIPL reports complete answers under 50 ms at peak load

> Liquid reports fast complete answers. Comparisons change both model and engine.

By BIGCHANGE.AI Editorial

Published: 2026-10-25T20:12:38.698Z
Updated: 2026-10-25T20:12:38.698Z
Canonical: https://bigchange.ai/blog/liquid-ripl-complete-response-latency-under-load

![Liquid wordmark on ivory.](https://bigchange.ai/api/media/file/liquid-ai-press-kit-wordmark-hero-v1.png)
Liquid AI.

Liquid AI introduced [RIPL](https://www.liquid.ai/blog/low-latency) (Real-time Inference Pipeline) on October 22. It reports complete generated answers under 50 milliseconds at continuous peak load.

## The big change

- **What changed:** Liquid times complete generated answers during sustained traffic.
- **Why it matters:** First-token speed omits the rest. Operators need completion p95 for their requests.
- **What to watch:** Enterprise GPU deployment requires sales contact. Buyers need comparable workload, quality and price evidence.

Liquid reports 14.4–28.4× lower p95 for LFM2.5-1.2B/RIPL against Qwen3.5-0.8B/vLLM, and 5.6–7.7× for its 2.6B pairing against Qwen3.5-2B. Both model and engine change, so RIPL's separate contribution is unresolved. The post does not establish full application latency. Liquid cites Shopify production use and sub-20 ms inference; its post supplies no independent customer measurement.

## Sources

- [RIPL announcement](https://www.liquid.ai/blog/low-latency) — Vendor benchmarks; enterprise access via sales.