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Groq develops AI inference processors built for real-time reasoning and ultra-low-latency performance.
Groq is an American AI semiconductor company founded in 2016 by Jonathan Ross, the lead architect behind Google’s Tensor Processing Unit (TPU). The company develops purpose-built AI inference hardware designed to deliver ultra-low latency and deterministic performance for large language models and other generative AI workloads. Rather than competing as a general-purpose chipmaker, Groq focuses exclusively on accelerating AI inference at scale. Its proprietary Language Processing Unit (LPU) architecture is optimized for high-throughput, real-time AI applications, enabling faster and more predictable inference than conventional GPU-based systems. As AI models become increasingly central to robotics and embodied intelligence, Groq’s hardware provides the compute infrastructure needed for responsive reasoning, multimodal perception, and autonomous decision-making.
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In December 2025, NVIDIA announced a ~$20 billion deal to license Groq's inference technology, validating that inference-optimized hardware represents an essential category in AI computing.
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Groq was founded in 2016 by Jonathan Ross, who had created Google's TPU as a side project. The company designed a novel statically-scheduled architecture delivering predictable, ultra-low latency performance.
Funding included $300 million Series C in 2021, $640 million Series D in August 2024 at $2.8 billion, and $750 million Series E in September 2025 at $6.9 billion. Total raised: ~$1.75 billion.
Groq gained attention in early 2024 with cloud API speeds of 500+ tokens/second, far outpacing GPU alternatives. The speed difference went viral among AI developers.
In December 2025, NVIDIA announced a ~$20 billion deal to license Groq's inference technology, validating that inference-optimized hardware represents an essential category in AI computing.