Mythic has engineered the Analog Processing Unit (APU) — a ground-up rethink of AI compute that moves memory inside the processor itself, eliminating the energy-draining data movement that makes conventional AI hardware unsustainable at scale.
The Problem Data transport accounts for 90% of the energy consumed by AI inference — a structural flaw baked into chip architectures dating back to the 1940s. As AI workloads explode, data centers face multi-gigawatt grid upgrades, ballooning costs, and regulatory pressure. Meanwhile, edge deployments — from autonomous vehicles to industrial sensors — are throttled by power envelopes that today’s GPUs routinely blow through.
What Makes It Different Using patented Analog-In-Memory Computing (AiMC), Mythic executes calculations directly inside flash memory using Ohm’s and Kirchhoff’s Laws — no data ping-pong, no cloud latency, no external memory bottleneck. The result: 120 TOPS per watt and a 100x performance-per-watt advantage over digital benchmarks. At 4 cents per million tokens for 1T parameter models, it undercuts Blackwell’s optimized 10 cents by more than half. The CAMP SDK ensures drop-in compatibility with PyTorch, TensorFlow, ONNX, and NVIDIA Jetson — no workflow overhaul required. Mythic is also Honda’s strategic partner for next-generation intelligent vehicle platforms.
Unlike competitors still simulating analog, Mythic ships production-ready silicon today.
When compute lives where the data lives, the energy bill — and the power crisis — shrinks with it.
Frequently asked questions
What is the main innovation of Mythic's technology?
Mythic's main innovation is the Analog Processing Unit (APU), which integrates memory inside the processor to reduce energy consumption.
How does Mythic's technology compare to traditional AI hardware?
Mythic's technology eliminates the energy-draining data movement found in conventional AI hardware, achieving a 100x performance-per-watt advantage.
