AutoPhi V18-Achievement -- Peak Series #572

Image SHA-256 — apv18-pea-0572-10nm.png
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SKU
APV18-PEA-0572-10NM
$7.6M

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AutoPhi V18 Peak 572 - Tera-class quantum-classical hybrid processor. 517.87 TFLOPS peak | 20.51 TOPS | 29827 qubits | 10nm | 3.0 W net power (self-sufficient) | 7/9 technologies. Patent Pending. COGS: $2.28M. IP Valuation: $253.46M. Foundry: Samsung 10LPE / TSMC N10.
First to market

Publicly online since 2010 · U.S. patent applications since 2012 · inventions offered since 2014. The work of Christopher Gabriel Brown, independently documented.

First posted: · Last updated:
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Instant download

Downloads immediately on checkout — the CD GDSII Generator (AES-256 encrypted). Open with 7-Zip, WinRAR, or macOS Archive Utility using password CRIONE99KEY. Founder Access Pass credit (code FAP99CREDIT) applies at checkout.

AutoPhi V18-Seed Voxel Processor -- Peak Series #636363

AutoPhi V18 Peak 572: 517.87 TFLOPS Tera-class | 10nm | 29827 Qubits | Maximum single-die performance

Overview

The AutoPhi V18 Peak 572 is a tera-class quantum-classical hybrid processor built on the 18-seed voxel DNA architecture at 10nm process technology. It delivers 517.87 TFLOPS peak performance with 20.51 TOPS AI acceleration across a 453x453 voxel grid (205,209 total voxels) stacked 67 layers deep (4 stack units of 18). Quantum subsystem: 29,827 qubits at 98.718% fidelity (error rate <1.282%) with 6,605 QEC-protected logical qubits. Clocked at 5.147 GHz with 28.98 TB/s memory bandwidth over 66 nanophotonic channels. Neuromorphic engine: 81.6K spiking neurons for event-driven AI processing. Power envelope: 320.7 W with 72% reduction vs 130nm baseline. Integrates 7/9 AutoPhi core technologies. Three-chromosome DNA encoding: 86-bit electron strand, 11 quantum instructions (atomic strand), 11 photon opcodes (light strand). Light-trigger initiated.

Key Specifications

Performance517.87 TFLOPS (Tera-class)
Process Node10nm
Clock Speed5.147 GHz
AI Acceleration20.51 TOPS
Quantum Subsystem29,827 qubits at 98.718% fidelity (error rate <1.282%)
QEC Logical Qubits6,605
Memory Bandwidth28.98 TB/s
Nanophotonic Channels66
Neuromorphic Engine81.6K spiking neurons
Power Envelope320.7 W
Power Reduction vs 130nm72%
Voxel Grid453x453 (205209 voxels, 67 layers, 4 stack units of 18)
Compute TypeCPU + full-GPU + DPU
Form FactorServer
LED Power Recycling86.8%
EM Cooling Efficiency82.3% (zero moving parts)
Quantum Battery Layers6
DNA Encoding86-bit electron strand, 11 quantum instructions, 11 photon opcodes
Instruction SetRed=ADD, Blue=SUB, Green=MUL, Yellow=DIV, Cyan=LOAD, Magenta=STORE, White=BRANCH, UV=QGATE, IR=SYNC, Orange=MEASURE, Violet=ENTANGLE

Target Markets

  • High-performance computing nodes
  • large-scale AI inference
  • climate modeling

Applications

  • Full AI model training
  • protein folding
  • nuclear simulation
  • real-time fraud detection at scale

Manufacturing & Fabrication

FoundrySamsung 10LPE / TSMC N10
PDK10nm PDK (NDA)
EDA FlowCommercial (Synopsys/Cadence)
ReadinessArchitecture Ready -- Awaiting 10nm PDK

Manufacturing Steps

  1. Obtain 10nm PDK under NDA
  2. Synthesize -> P&R -> DRC/LVS
  3. Package per FOUNDRY_STANDARDS.md
  4. Submit via foundry portal

Deliverables

  • GDSII (mask layout)
  • LEF (library exchange)
  • DEF (design exchange)
  • Gate-level netlist (Verilog)
  • DRC report
  • LVS report
  • FOUNDRY_HANDOFF_SIMPLE.txt
  • RTL (autophi_light_cpu_core.v + autophi_quantum_cpu_core.v + autophi_hybrid_cpu_top.v)
  • Synthesis scripts
  • P&R configurations
  • Manufacturing documentation
  • Performance projections

RTL Design Files

  • autophi_light_cpu_core.v
  • autophi_quantum_cpu_core.v
  • autophi_hybrid_cpu_top.v

Acquisition Path

This product is available through CGB's 4-step acquisition path. The current price is shown in your cart and on the live storefront page.

  • Step 1 — Proof of Function: public, $1.69 each.
  • Step 2 — Mathematical Deposition: reading material under mutual NDA.
  • Step 3 — Evaluation License: hands-on evaluation under NDA; fee credits toward Step 4.
  • Step 4 — Full Acquisition:

See the acquisition path overview →

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