With $125 Mn haul, Mythic Wants to Take on NVIDIA GPUs with 100x Energy-Efficient AI Chips

Mythic, a Palo Alto-based AI chip company, has raised $125 million in a funding round to develop analog processing units designed to cut AI energy use by up to 100x compared with GPUs. 

The round was led by deep tech-focused venture capital firm DCVC and will support Mythic’s product development, software, and commercial scale-up efforts.

NEA, Atreides, Future Ventures, Softbank KR, S3 Ventures, Linse Capital, One Madison Group, and Catapult, along with Honda Motor and Lockheed Martin, also joined the round.

The company said the raise follows a restructuring under chief executive officer Taner Ozcelik (former NVIDIA VP and GM), and focuses on addressing power constraints in AI computing. “Energy efficiency will define the future of AI computing everywhere,” Ozcelik said in a statement. 

Mythic plans to deploy its chips across data centres, automotive systems, robotics, and defence. The 13-year-old company will also use the funding to rebuild its architecture, software stack, and strategy.

The company also introduced Starlight, a sub-one-watt sensing platform that integrates its chips into image sensors. Mythic said the system improves signal extraction in low-light conditions and targets defence, automotive, and robotics use cases.

Mythic’s chips are manufactured in the United States and allied countries using standard semiconductor processes. The company plans to use the new capital to expand production, mature its software development kit, and pursue commercial deployments in AI inference markets.

Mythic’s chips use analog in-memory computing, which combines memory and processing in a single plane. The company said this design reduces energy loss during data movement, which it claims accounts for most of the power consumption in current AI systems. 

According to Mythic, its current architecture delivers 120 trillion operations per second per watt.

Ozcelik said the company aims to complement GPUs rather than replace them. “Much as GPUs became the accelerated computer of choice next to CPUs, our APUs will become the accelerated computer of choice next to GPUs,” he said.

Mythic said its chips can run large language models with up to one trillion parameters without requiring high-speed interconnects used by GPU clusters. Internal benchmarks cited by the company show higher tokens per second per watt compared with current high-end GPUs.

Aaron Jacobson, partner at NEA, said the platform “collapses today’s limits on energy and cost” and gives the company scope to scale. Steve Jurvetson of Future Ventures said Mythic’s approach unifies computation and memory “as in the brain,” improving efficiency.