Groq is no longer in the active top-40 roster for this sector — snapshot as of August 19, 2026. News and free pipes continue to update; predictions, hard problems, theses and other authored fields are frozen at the date above.
Groq is an AI Accelerators company founded in 2016 and based in Mountain View, USA. It has raised $2.0B in total funding, most recently a Series F in 2026 at a $3.5B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Aug 17, 2026 | Series F | $350M | $3.5B | Nvidia |
| Sep 17, 2025 | Series E | $750M | $6.9B |
| Disruptive |
| Aug 1, 2024 | Series D | $640M | $2.8B | BlackRock |
| Apr 1, 2021 | Series C | $300M | $1B | Tiger Global Management, D1 Capital Partners |
| Jan 1, 2017 | Seed | $10M | — | Social Capital |
A purpose-built AI inference chip using a deterministic, software-scheduled architecture with large on-chip SRAM instead of external HBM, eliminating the memory bottlenecks that limit GPUs on token generation. Designed by ex-Google TPU lead Jonathan Ross, the LPU delivers extremely low, predictable latency for large language models. It is Groq's core silicon and the basis for the fastest publicly measured LLM inference speeds.
A developer-facing inference cloud that serves popular open models (Llama, Mixtral, Whisper, and others) at very high tokens-per-second over an OpenAI-compatible API. GroqCloud lets developers tap LPU performance without owning hardware and is Groq's primary commercial channel, with usage-based pricing. It remains the company's flagship service and continues operating after the December 2025 Nvidia deal.
Rack-scale systems that interconnect many LPUs into a deterministic compute fabric for customers who need on-premise or sovereign inference deployments. GroqRack scales the LPU architecture beyond a single chip for high-throughput, low-latency serving of large models in private data centers, extending Groq's offering from cloud API access to dedicated enterprise and government installations.
21 patents on file, but none with both an extractable figure and an abstract on Google Patents yet.