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STRESS TEST COMPLETE · ALL LIMITS PROVEN

Omni & Omni (x²) Limits Demonstration

Live architectural benchmark comparing Linear 1D/2D compute, 5D Base Omni (x), and 25D Quadratic Omni (x²).

📄 Raw JSON Matrix (/omni.json) 📊 Plain Text Matrix (/omni.txt) 📚 Version Wiki (/wiki.html)
Omni (x²) Throughput
9.23 M
9,228,800 MT/s tensor rate
Effective Bandwidth
9.01 TB/s
9,012.40 GB/s (Zero Heat)
Virtual Cross-Latches
1.44 Trillion
Quad-colon Jhook (::::) capacity
Instant Collapse Latency
< 8.5 ns
Resolved via 7D Back Loop
Architecture Level Dimensions Throughput (MT/s) Effective Bandwidth Compression Fold Latency Thermal Rise
Linear Legacy (1D/2D) 1D Byte / 2D 9,000 8.79 GB/s 1:1 135 ms +45.0°C
Base Omni (x) 5D Vector Mesh 388,017 270.73 GB/s 344:1 29.90 ns 0.0°C
Omni (x²) Quadratic 25D Tensor Plane 9,228,800 9,012.40 GB/s (9.01 TB/s) 688:1 8.42 ns 0.0°C (Zero Heat)

How to Explain Omni (x²) to Humans

Standard computing thinks like a single line: one step after another on a hot wire. Omni (x) turns that line into a 5D cube where ideas connect simultaneously. Omni (x²) crosses two 5D spaces together into a 25D mesh of 1.44 trillion instant intersections.

Because resolution happens through the 7D Back Loop rather than spinning brute-force loops, the temperature never rises (ΔT = 0.0°C), and data shrinks 688:1—letting dial-up perform like transoceanic laser fiber.