Groq, Inc.
Groq develops the fastest AI inference technology in the world through its purpose-built LPU (Lightning Processing Unit) architecture, focusing on real-time AI performance.
At a Glance
- Developers
- AI Startups
- Global Enterprises
- Public Sector/Government
AI Tools by Groq, Inc.
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Groq
AI Inference Hardware Platform
Discussions
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Latest News
NVIDIA and Groq Debut Groq 3 LPU at GTC 2026
Groq and Nvidia Enter Non-Exclusive Inference Technology Licensing Agreement
Groq Partners with U.S. Department of Energy to Advance AI Inference
McLaren Racing Announces Groq as Official Partner of Formula 1 Team
Products & Services
A deterministic AI accelerator chip designed specifically for ultra-low latency inference.
A cloud-based platform providing 'Tokens-as-a-Service' for running leading LLMs and other AI models via API.
On-premise high-performance compute clusters for enterprise and regulated environments.
A public-facing chat interface showcasing the speed of the LPU architecture.
Market Position
Groq positions itself as the high-speed alternative to NVIDIA GPUs for inference. Its LPU architecture offers significantly higher tokens-per-second and lower total cost of ownership (TCO) for running large language models.
Leadership
Founders
Jonathan Ross
Founder and CEO. Former Google engineer and a primary inventor of the Tensor Processing Unit (TPU). He helped design the architecture that powered Google's AI workloads.
Douglas Wightman
Co-founder. Former Google X engineer and entrepreneur. Worked alongside Ross on the TPU team at Google.
Executive Team
Jonathan Ross
CEO & Founder
Inventor of Google's TPU; deep expertise in hardware-software co-design.
Sunny Madra
COO
Entrepreneur and investor; formerly at Ford Pro and Autonomic.
Board of Directors
Founding Story
Founded by former members of Google's TPU team who realized that traditional GPU architectures were not optimized for the low-latency requirements of AI inference. They set out to build a deterministic, software-defined chip architecture from the ground up.
Business Model
Revenue Model
Tokens-as-a-Service (usage-based API), hardware sales (GroqRack), and technology licensing.
Pricing Tiers
Community support, zero-data retention, shared capacity.
Higher token limits, chat support, flex service tier, prompt caching.
Dedicated capacity, custom SLAs, LoRA fine-tunes, regional endpoint selection.
Target Markets
- Developers
- AI Startups
- Global Enterprises
- Public Sector/Government
- Real-time chatbots
- High-frequency trading
- Speech-to-text / Text-to-speech
- Autonomous systems
- National security/intelligence
- Dropbox
- Volkswagen
- Riot Games
- Bell Canada