Run heavy AI pipelines, render complex 3D timelines, and accelerate dense graphics workloads natively across host CPU hardware frameworks. Eliminate unrecoverable out-of-memory application crashes using our uncapped Infinite Virtual VRAM System Memory Pooling engine.
One of the core design goals behind Nexus was "Frictionless Deployment." The suite operates cleanly in local user scope (AppData/Local), meaning zero global path corruption and zero administrative elevation blocks.
As local AI modelers, LLM deployers, and machine learning architects, we are constantly clashing against a rigid physical boundary: CUDA out-of-memory driver crashes during heavy inference or vector database processing.
If you are running complex Blender viewports or dense WebGL material nodes, you know the absolute frustration of hitting your card's memory limits mid-calculation and watching your rendering app instantly freeze or vanish from your screen.
I’m Fabian Robert Florrice, the Founder and Lead Systems Architect at Nexus OmniCore Laboratories. I am incredibly proud to introduce Nexus Virtual GPU Suite to the world today!
As a researcher, strategist, and a digital creator/video editor, I kept hitting a massive, unyielding wall in my daily workstation workflows: unrecoverable out-of-memory (OOM) application driver crashes. Whether I was rendering dense material nodes in 3D timelines or processing heavy local AI inference matrices, the choice was always the same — throw thousands of dollars at localized hardware upgrades or rent high-latency, expensive cloud computing instances that throttle data-transfer loops.
I knew there had to be a cleaner, native approach. The problem isn’t a lack of physical system memory on our rigs; it is how sandboxed applications handle hardware allocation boundaries.
So, I built Nexus from the ground up using raw, low-overhead Win32 and native C++. No Electron bloat, zero background telemetry tracking, and entirely deployable inside local user scope (AppData\Local) with absolute zero administrative elevation blocks.
How it works under the hood:
Nexus utilizes a native cross-process memory handshake to force-inject specialized dynamic link library shims (opengl32.dll / nvcuda.dll) directly into running process trees (like Google Chrome). It dynamically pools your standard physical system RAM into an uncapped virtual VRAM scratchpad layer.
To clear heavy calculation paths:
• Standard Pro Tier (v1.0.0): Employs parallel 256-bit AVX2 SIMD matrix routing to clear massive float transforms in 113ms on standard creator rigs.
• Advanced Enterprise Pro (v2.0.0): Unlocks full 16-parallel lane 512-bit AVX-512 registers, swallowing a 16-million floating-point matrix transformation pass in an absolute sub-33ms locally.
We value technical transparency above all else. You can visually watch individual CPU threads spike and drop into active computing blocks inside Windows Task Manager's 'Logical Processors' view on your command click. Better yet, we’ve included a native PowerShell module audit query right in our manuals so you can verify bit-for-bit module attachment inside Chrome's memory tree yourself.
To celebrate our Product Hunt launch day, we are offering an exclusive 15% OFF recurring monthly launch discount for the community! Enter code OMNICORE15 at checkout to lock in your developer privileges forever:
I will be active here in the comment section all day long. I would love to hear your feedback, discuss local performance architecture optimization, or answer any technical engineering questions you have.
🚀 Hello Product Hunt community!
I’m Fabian Robert Florrice, the Founder and Lead Systems Architect at Nexus OmniCore Laboratories. I am incredibly proud to introduce Nexus Virtual GPU Suite to the world today!
As a researcher, strategist, and a digital creator/video editor, I kept hitting a massive, unyielding wall in my daily workstation workflows: unrecoverable out-of-memory (OOM) application driver crashes. Whether I was rendering dense material nodes in 3D timelines or processing heavy local AI inference matrices, the choice was always the same — throw thousands of dollars at localized hardware upgrades or rent high-latency, expensive cloud computing instances that throttle data-transfer loops.
I knew there had to be a cleaner, native approach. The problem isn’t a lack of physical system memory on our rigs; it is how sandboxed applications handle hardware allocation boundaries.
So, I built Nexus from the ground up using raw, low-overhead Win32 and native C++. No Electron bloat, zero background telemetry tracking, and entirely deployable inside local user scope (AppData\Local) with absolute zero administrative elevation blocks.
How it works under the hood:
Nexus utilizes a native cross-process memory handshake to force-inject specialized dynamic link library shims (opengl32.dll / nvcuda.dll) directly into running process trees (like Google Chrome). It dynamically pools your standard physical system RAM into an uncapped virtual VRAM scratchpad layer.
To clear heavy calculation paths:
• Standard Pro Tier (v1.0.0): Employs parallel 256-bit AVX2 SIMD matrix routing to clear massive float transforms in 113ms on standard creator rigs.
• Advanced Enterprise Pro (v2.0.0): Unlocks full 16-parallel lane 512-bit AVX-512 registers, swallowing a 16-million floating-point matrix transformation pass in an absolute sub-33ms locally.
We value technical transparency above all else. You can visually watch individual CPU threads spike and drop into active computing blocks inside Windows Task Manager's 'Logical Processors' view on your command click. Better yet, we’ve included a native PowerShell module audit query right in our manuals so you can verify bit-for-bit module attachment inside Chrome's memory tree yourself.
To celebrate our Product Hunt launch day, we are offering an exclusive 15% OFF recurring monthly launch discount for the community! Enter code OMNICORE15 at checkout to lock in your developer privileges forever:
👉 https://nexus-virtual-gpu-pro.netlify.app/
I will be active here in the comment section all day long. I would love to hear your feedback, discuss local performance architecture optimization, or answer any technical engineering questions you have.
Let the computing acceleration begin! ⚡