Groq

Groq

by Groq
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Summary

Inference on custom LPU hardware, built for latency — open models served at speeds general-purpose GPUs struggle to match.

Description

Groq runs open-weight language models on its own Language Processing Unit rather than on GPUs, and the whole product is organised around one property: tokens come back fast. For applications where a user is waiting — voice agents, live translation, interactive assistants — the difference between a stream that trickles and one that arrives instantly changes what you can build.

What it offers

  • GroqCloud, an OpenAI-compatible API serving popular open models, so migrating an existing integration is usually a base-URL change
  • Very high token throughput at low latency, which makes multi-step agent loops and real-time speech pipelines practical
  • Predictable per-token pricing with a free tier for evaluation
  • Speech models alongside text, for transcription and voice-first products

When it is the right call

Choose Groq when response time is the product requirement rather than a nice-to-have, and when an open-weight model is good enough for the task. Teams often pair it with a frontier model — the fast path handles the interactive turn, and the slower, stronger model handles work that can happen in the background.

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