Ranked by most recently funded · 25 of 40 on the roster
Cerebras builds wafer-scale AI chips with millions of cores optimized for large-scale model training and inference.
SiFive licenses RISC-V processor IP and builds custom silicon solutions for AI, automotive, and data-center customers.
SiMa.ai builds a software-centric edge-AI 'MLSoC' that runs computer-vision and ML workloads at low power for the embedded edge.
Rebellions is a Korean AI-chip unicorn behind the ATOM and REBEL inference accelerators, formed by its 2024 merger with SK Telecom's Sapeon.
Ayar Labs develops chiplet-based optical I/O solutions that replace electrical interconnects in AI and HPC systems.
Axelera AI is a European edge-AI startup whose Metis chips use in-memory computing to run computer-vision inference at low power and cost.
MatX, founded by ex-Google TPU engineers, designs chips optimized specifically for large language models, with first silicon due in 2027.
SambaNova builds dataflow AI accelerators and full-stack software for enterprise AI training and inference at scale.
Positron AI builds energy-efficient LLM inference appliances (Atlas) as a US-made, memory-bandwidth-optimized alternative to GPUs.
Etched builds application-specific chips hardwired to run transformer architectures with extreme performance and efficiency.
Mythic develops analog compute-in-memory chips for edge AI inference, targeting industrial, defense, and automotive applications.
d-Matrix builds in-memory compute chips optimized for efficient transformer inference at scale in data centers.
Groq builds Language Processing Units (LPUs) for ultra-low-latency LLM inference — the tech behind Nvidia's reported ~$20B Dec 2025 IP deal.
FuriosaAI is a Korean startup building energy-efficient AI inference chips (RNGD); it rebuffed an ~$800M Meta buyout to stay independent.
EnCharge AI develops in-memory compute chips for ultra-efficient AI inference at the edge and in data centers.
Tenstorrent designs open-source RISC-V AI processors and licenses chiplet IP for scalable AI compute.
Lightmatter builds photonic processors and optical interconnects to accelerate AI compute and reduce data-center power consumption.
Hailo builds edge AI processors optimized for computer vision and neural network inference in automotive and industrial devices.
Astera Labs builds high-speed connectivity silicon — retimers, CXL controllers, and fabric switches — for AI and cloud data centers.
Arm licenses CPU architectures and IP used in nearly every mobile device and increasingly in data-center and AI chips.
GlobalFoundries operates fabs focused on specialty and mature-node semiconductors for automotive, IoT, and RF applications.
Navitas manufactures gallium nitride (GaN) power semiconductors that increase efficiency in data-center power supplies and AI systems.
Ambarella (NASDAQ: AMBA) designs low-power edge-AI vision SoCs — CV3-AD and N1 — for automotive ADAS, security cameras, and robotics.
Broadcom designs custom AI accelerators for hyperscalers (Google TPU) and supplies networking silicon critical to AI cluster interconnects.
Marvell designs custom AI silicon for hyperscalers and supplies data-center networking, storage, and interconnect chips.
