Custom Silicon

Oracle Class

Purpose-built silicon for frontier intelligence.

Not GPUs repurposed. Silicon designed from first principles for AI inference. The W1 architecture: spatial dataflow, 96GB HBM3E, 256MB distributed SRAM. 3nm process. Cars, drones, planes, operating systems — anything that runs on silicon, runs on Oracle Class.

4.8 TB/s

memory bandwidth

40%

energy reduction

85ms

time to first token

3nm

process node

Capability Map

W1 connects to: Spatial Dataflow, HBM3E Memory, Distributed SRAM, Mesh Interconnect.

Oracle Class's W1 architecture spans four silicon capability domains.

Architecture

Design principles

GPUs waste silicon on training-grade precision

→

W1 uses flexible per-layer precision — INT4 to FP16 where it matters

Memory bandwidth is a physics problem

→

12-stack HBM3E with 4096-bit interfaces: 4.8 TB/s

Scale requires data center infrastructure

→

4-chip W1 serves 1T parameters at 52 tok/s per user

Energy efficiency means slower inference

→

1.87 J/token vs 3.14 J/token on commodity GPUs — faster AND greener

Applications

Autonomous vehicles

Real-time inference at 85ms. No cloud roundtrip. Oracle Class runs Odyssey locally in the vehicle.

Drone fleets

Edge intelligence for swarm coordination. Object Class perception on Oracle Class silicon.

Operating systems

Local AI inference as a first-class OS capability. No API calls, no latency, no privacy leaks.

“The memory wall is a physics problem. We solved it with architecture.”

— Webbeon Silicon Team

In The Field

Real results

W1 FPGA Prototype

85ms TTFT, 210 tok/s on Odyssey. Commodity GPU: 320ms, 74 tok/s.

Energy

1.87 J/token vs 3.14 J/token. At 1B tokens/day: 14.7 kW continuous savings.

Scale

4-chip config serves 1T parameters. 1.6 TB/s inter-chip bandwidth.

How It Connects

One architecture

Odyssey

Oracle Class runs Odyssey natively. Intelligence at the speed of silicon.

Learn more →

Object Class

Oracle Class powers Object Class at the edge. Perception without the cloud.