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Blazing-fast LLM inference on custom LPU chips
Groq runs Llama, Mixtral, Gemma, and other open models on its own custom Language Processing Unit chips, purpose-built for sequential token generation, and the result is inference speed that's typically 10-20x faster than GPU-based cloud providers. Developers use its API as a near drop-in OpenAI replacement wherever latency actually matters — real-time voice apps, low-latency agent pipelines — where a slow model response breaks the whole experience.
Amelia Ryan
Been using this for about half a year. Dashboard is clunky compared to the API itself. Had one outage that cost us a bad afternoon.
Grace Otieno
Been using this for about a month. It's fine for what I need most days. Had one outage that cost us a bad afternoon.
Elena Sergeeva
Does exactly what it promises.
Maximilian Schulz
Tried it after a coworker recommended it. It's fine for what I need most days.
Fatma Ali
Switched over from a competitor a month ago. Docs are clear enough that I got it running the same day. Rate limits kicked in earlier than the docs suggested.
Tatiana Zaitseva
It's okay, does the job.
Emeka Chukwu
Picked this up for a side project and kept using it. Latency has been solid even under load.
Julia Navarro
Picked this up for a side project and kept using it. Pricing is predictable, no surprise bills so far.
Maria Dominguez
Tried it after a coworker recommended it. Latency has been solid even under load.
Charlie Evans
Tried it after a coworker recommended it. It's fine for what I need most days. Dashboard is clunky compared to the API itself.
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