Groq vs Modular AI

By valuation, Groq is the larger company at $20B versus $1.6B — a 12.5x difference. Size can also be measured by team: Groq employs 300 people while Modular AI has 150 employees.

Groq has raised more in total funding at $1.4B, compared to Modular AI's $380M — a gap of $1B. Combined, the two companies have completed 8 known funding rounds.

Groq leads with an Awaira Score of 80/100, while Modular AI sits at 76/100. That 4-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Groq was founded by Jonathan Ross in 2016. Modular AI was founded by Chris Lattner in 2022. Visit each company's profile on Awaira for a full founder biography.

Groq: Groq is an AI infrastructure company founded in 2016 that designs and manufactures specialized processors for artificial intelligence workloads. The company's core product is the Language Processing Unit (LPU), a custom-built chip architecture optimized for inference tasks in large language models and other AI applications. Unlike traditional GPUs designed for general-purpose computing, Groq's LPUs prioritize deterministic latency and throughput for sequential AI processing, enabling faster token generation in inference scenarios. Groq has positioned itself as an alternative to NVIDIA's GPU-dominated infrastructure market, targeting enterprises requiring high-performance AI inference at scale. The company offers cloud-based access to its hardware through GroqCloud, allowing developers to run inference workloads with reduced latency compared to conventional GPU implementations. Groq operates in the competitive AI infrastructure sector, competing with established players like NVIDIA, as well as emerging alternatives including custom chip manufacturers and cloud providers developing proprietary AI accelerators. In December 2025, Nvidia and Groq announced an agreement reportedly valued at approximately $20 billion to license Groq's AI inference technology. Groq's growth trajectory reflects increasing enterprise demand for efficient inference infrastructure. Groq's LPU architecture specifically optimizes for inference latency rather than training, addressing a distinct performance bottleneck in deployed AI systems. Groq operates in the AI Infrastructure sector and is headquartered in United States. Founded in 2016 by Jonathan Ross, Groq has raised $1.4B in total funding, achieving a valuation of $20B as of its latest round. The company's funding journey includes a Series A of $30M in 2019, a Series B of $40M in 2021, a Series C of $300M in 2021, a Series D of $450M in 2023. The most recent round was led by SoftBank Vision Fund 2. With approximately 300 employees, Groq has established itself as a Acquired-stage player in the AI Infrastructure market. The company holds an Awaira Score of 80/100, reflecting its strong position across valuation, funding trajectory, team scale, and market influence. Groq competes in a rapidly evolving segment alongside other AI Infrastructure companies. Based in United States, Groq is part of a growing international AI ecosystem attracting talent and investment. The AI Infrastructure space has attracted significant investment in recent years, with companies racing to capture enterprise and consumer demand for AI-powered solutions. Modular AI: Modular AI, founded in 2022 and valued at $1.6 billion, develops infrastructure software for AI systems. The company has raised $380 million in Series C funding. Modular AI's core focus is building compiler and runtime technologies that optimize AI model execution across diverse hardware platforms. The company's primary product is Mojo, a programming language designed to bridge the gap between research and production AI systems, enabling developers to write performant code without switching between multiple languages. Mojo combines Python's accessibility with systems programming capabilities, targeting the inefficiencies in traditional AI development workflows. The platform addresses a critical pain point in AI infrastructure: the fragmentation between high-level ML frameworks and low-level optimization requirements. Modular AI positions itself within the growing AI infrastructure layer, competing alongside companies focused on model optimization, deployment, and hardware abstraction. The company operates in a competitive landscape that includes established players in compiler technology and emerging AI infrastructure vendors. Modular AI's approach emphasizes developer productivity and hardware portability, allowing AI engineers to optimize code for various accelerators and processors. The company's growth trajectory reflects broader demand for specialized infrastructure solutions as enterprise AI adoption accelerates. Specific customer deployments are not widely disclosed, though the company targets enterprises seeking deployment flexibility and performance optimization. Modular AI develops Mojo, a systems programming language designed to unify AI research and production workflows by eliminating language switching friction.

Groq got there first, launching in 2016 — that's 6 years of extra runway. Modular AI didn't arrive until 2022. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Groq has about 300 employees; Modular AI has about 150. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Groq and Modular AI compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.