Liquid AI Launches RIPL Real-Time Inference Engine
Liquid AI debuts RIPL, a real-time inference engine delivering sub-50 ms latency for LFM models, outperforming vLLM benchmarks on B200 chips.
Stock photo for illustration only, not from the actual event
- Liquid AI introduces RIPL, a new real-time inference engine for LFMs.
- Engineered to achieve sub-50 ms processing latency.
- Outperforms Qwen3.5-0.8B on vLLM when tested on a single B200 chip.
Liquid AI has officially rolled out RIPL, a high-performance inference engine built specifically to accelerate its proprietary LFM models. The new software solution focuses on achieving ultra-fast real-time processing capabilities, targeting response times well under the 50-millisecond threshold.
The company demonstrated the capabilities of RIPL through rigorous benchmarking tests, utilizing a single B200 hardware accelerator running the LFM2.5-1.2B model configuration to measure real-world performance gains.
Test results revealed a substantial performance advantage, showing that the LFM setup on RIPL achieved a p95 latency between 14.4 and 28.4 times lower than the Qwen3.5-0.8B model running on the vLLM framework under the same conditions.
Stock photo for illustration only, not from the actual event
The introduction of RIPL highlights Liquid AI's strategic focus on optimizing inference efficiency for edge and real-time deployment scenarios. By cutting latency down to sub-50 ms levels, developers can build more responsive AI applications such as voice assistants and interactive robotics that require instantaneous feedback, moving beyond the traditional trade-offs of larger transformer models.
Source: MarkTechPost
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