Groq Raises $640 Million to Scale AI Inference Platform’s Capacity

Groq has raised $640 million in a Series D funding round to scale the capacity of its vertically integrated artificial intelligence (AI) inference platform. The company will also use the new funding to add talent and accelerate the development of the next generation of language processing units (LPUs), according to a Monday (Aug. 5) press […]

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Groq has raised $640 million in a Series D funding round to scale the capacity of its vertically integrated artificial intelligence (AI) inference platform.

The company will also use the new funding to add talent and accelerate the development of the next generation of language processing units (LPUs), according to a Monday (Aug. 5) press release.

“We intend to make the resources available so that anyone can create cutting-edge AI products, not just the largest tech companies,” Jonathan Ross, CEO and founder of Groq, said in the release. “This funding will enable us to deploy more than 100,000 additional LPUs into GroqCloud.”

GroqCloud is currently being used by more than 360,000 developers who are building on the platform and creating AI applications on openly available models like Meta’s Llama 3.1, OpenAI’s Whisper Large V3, Google’s Gemma and Mistral’s Mixtral, according to the release.

With the new funding, Groq will scale the capacity of its tokens-as-a-service (TaaS) offering and add new models and features to GroqCloud, the release said.

Groq’s latest funding round was led by funds and accounts managed by BlackRock Private Equity Partners, per the release.

“The market for AI compute is meaningful and Groq’s vertically integrated solution is well positioned to meet this opportunity,” Samir Menon, managing director at BlackRock Private Equity Partners, said in the release. “We look forward to supporting Groq as they scale to meet demand and accelerate their innovation further.”

There is a critical need for next-generation systems for AI inference solutions that can boost performance and power efficiency while offering the lowest total cost of ownership, PYMNTS reported in May. This comes as AI training costs typically reach hundred of millions of dollars.

In July, San Francisco Compute Co. raised $12 million in an early funding round to launch a trading platform for computing power. With the platform, the company aims to help companies working with AI meet the challenge of getting access to the semiconductors they need.

In February, Recogni secured $102 million in a Series C funding round to drive the development of next-generation systems for AI inference solutions that aim to significantly boost performance and power efficiency while offering the lowest total cost of ownership.

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