Groq

advancedspreading

Groq is a US chip company whose own-designed processors, called LPUs, serve language model responses much faster than usual.

In plain terms

When you ask an AI chatbot a question, computers in a data center generate the answer. This work is called inference, and it determines whether the text flows slowly or appears almost instantly. Groq builds chips specifically for this task and rents them out as a cloud service.

Imagine it like a kitchen. The traditional graphics chip (GPU) is like a chef who can cook anything, from training to image generation. The Groq LPU is like a kitchen production line that prepares only one type of dish, but does so very quickly and at a predictable pace.

Groq does not create its own language model. It runs other freely available (open) models, such as Meta's Llama family or OpenAI's publicly released models. What it offers is that the same model responds faster on its platform.

Speed truly matters where waiting is disruptive: in voice assistants, live customer service, or when an agent performs many steps in a row and the delay of each step adds up.

How it works

The language model assembles the response from small text fragments, tokens, one after another. Speed is therefore measured by how many tokens are generated per second.
The LPU (Language Processing Unit) is designed specifically for this sequential, step-by-step work: the memory is on the chip itself, so data does not need to travel back and forth from external memory.
A compiler program plans the exact schedule of calculations in advance. Because of this, the chip does not decide what comes next while running, and the response time remains uniform.
A large model connects many LPUs, which pass partial results to each other like an assembly line.
Developers access all this via a service called GroqCloud: they send the request over the internet and receive the ready answer; they do not need to buy the chip.

An everyday example

You call customer service by phone, where an AI voice assistant answers, and there is no awkward two- or three-second silence after your sentence. It is quite possible that a Groq-style fast server is working in the background. You do not encounter the company's name, only feel that the conversation flows at a natural pace.

Who is affected

developerIf you build a real-time application or a multi-step agent, Groq's fast inference can noticeably shorten wait times. → Code

entrepreneur, executiveThe cost and customer experience of an AI service are influenced by the infrastructure the model runs on, not just which model you choose.

bank customer, investorGroq was long in the news as one of Nvidia's best-known challengers; since the end of 2025 it has been mentioned more often for its licensing agreement with Nvidia, which shows how much fast serving has gained in value in the AI chip market. → Money

everyoneSome voice and chat AI services respond almost without delay because chips purpose-built for fast serving work in the background.

A common misconception

MythGroq is the same as Grok, Elon Musk's chatbot.

In realityThe two names only sound alike. Groq (with a 'q') is a company that builds chips and a cloud for serving models, while Grok (with a 'k') is xAI's language model and chatbot.

Limits and risks

The LPU is for running trained models, not for training new ones, where GPUs still dominate.
You can only access models that Groq has added to its offering; closed top-tier models (such as the Claude or Gemini families) do not run on it.
A quick answer is not a smarter answer: the model can still be wrong, just faster.
As a cloud service, your data passes through an external company's servers, so for sensitive data, check where the data center is located and what the contract states.

Similar, but not the same

Grok – Grok is the xAI chatbot and language model, while Groq provides hardware and server infrastructure for other people's models.
GPU – The GPU is a general-purpose accelerator suitable for both training and inference, while the LPU is a dedicated chip designed for fast inference of ready-made AI models, primarily language models, but not for training.
Nvidia – Nvidia is the market leader, a giant offering chips for almost every AI task, while Groq is a smaller company specialized in a narrow area: fast inference. Since the end of 2025, they have not been merely competitors: Nvidia has licensed Groq's technology.

Related concepts

Broader

AI chip, AI infrastructure, semiconductor industry

Narrower

LPU, GroqCloud

On the edge

Nvidia, Cerebras, GPU, inference, token

A brief history

Groq was founded in 2016 by Jonathan Ross and a few associates; Ross previously worked on developing Google's own AI chip, the TPU. The company became widely known in 2024, when in its public demonstrations language models responded at speeds that had been unusual until then. In late 2025, Nvidia signed a licensing agreement for Groq's technology, and the founder, along with several executives, joined Nvidia.

Where things stand

Many developers use GroqCloud for applications built on fast, open models, but compared to the entire market, it remains a niche product alongside GPUs. At the end of 2025, Nvidia signed a non-exclusive licensing agreement for Groq technology, and several of the company's leaders, including founder Jonathan Ross, moved there. Groq continues to operate as an independent company with new leadership and has retained its cloud service.

Status: 2026 November

Also known as

Groq · Groq Inc. · GroqCloud · LPU · Language Processing Unit · language processing unit · Groq-chip · GroqChip

Sources

This entry was machine-edited and has undergone machine expert review; the “In the news” section updates automatically from Agent Age stories.