When sub-100ms LLM response is the goal, Groq's dedicated inference hardware makes it possible.
Voice AI is a real-time medium. Every millisecond of LLM inference time is a millisecond of silence between what the caller says and what the agent responds. Groq's Language Processing Units (LPUs) deliver LLM inference 10-50x faster than GPU-based systems — making it the fastest available conversation engine for Fluents deployments where response latency is the primary optimization target.
For high-frequency trading firms, emergency services applications, or any use case where conversational flow must feel instant, Groq is the choice.
Groq's LPU hardware delivers LLM inference at speeds 10-50x faster than GPU-based systems — reducing the pause between caller and agent to near-imperceptible levels
Consistent low latency at scale — Groq's hardware architecture avoids the variable latency spikes common with GPU inference under load
Available as the conversation engine for Fluents deployments where conversational flow quality is the top optimization target
How LPUs Change the Latency Equation
Traditional GPU-based LLM inference involves significant overhead from memory bandwidth constraints and batch scheduling. Groq's LPU architecture is purpose-built for sequential token generation — the exact workload of a real-time conversation. The result is consistent sub-100ms inference for many model sizes, compared to 300-800ms typical for GPU inference.
High-Volume Call Centers: Naturalness at Scale
A contact center running thousands of simultaneous Fluents calls needs each call to feel like a natural conversation. With GPU inference, latency can spike when infrastructure is under load. Groq's hardware delivers consistent sub-100ms response regardless of concurrent call volume — so the 1,000th simultaneous call feels as natural as the first.
Urgent Use Cases: Medical Triage, Emergency Dispatch
Not all AI calls are routine. Medical triage lines, emergency callback systems, and crisis intervention applications require agents that respond instantly. A noticeable pause before the agent speaks is unacceptable when a patient is describing chest pain. Groq's latency profile makes Fluents suitable for time-critical communication contexts that other LLM configurations can't meet.