GP2 — Flagship GPU CFD Node with 96 GB vRAM for Large-Scale ANSYS Fluent Solves

The GP2 node is our top-tier GPU platform for ANSYS Fluent, built around the NVIDIA RTX PRO 6000 Blackwell Max-Q with a remarkable 96 GB of GDDR7 vRAM — enough to run very large cases entirely on the GPU. Backed by a 24-core Intel® Xeon® Gold CPU and 256 GB of system RAM, GP2 removes the usual ceilings: massive GPU memory for the native GPU solver, abundant system memory for large CPU-side meshes, and 3511 TFLOPS of tensor performance driving it all. When your case is large, demanding, and you want maximum acceleration, GP2 is the top of the range.

It is the no-compromise GPU tier in our lineup: the largest GPU memory we offer, a generous 256 GB memory budget, and modern flagship compute — built for the cases that overwhelm smaller nodes.

Specifications

GP2 leads with the largest GPU memory in our range: 96 GB of GDDR7 on the RTX PRO 6000 Blackwell Max-Q, delivering 3511 TFLOPS of tensor performance — purpose-built to run Fluent's native GPU solver on large, supported cases without spilling beyond the card. Behind it, a 24-core Xeon Gold 5412U (up to 3.9 GHz turbo, 45 MB cache) and 256 GB of system RAM handle very large meshing and CPU-side solving, with fast datacenter SSDs for responsive I/O.

What's included with GP2

Every GP2 rental comes with extras to help you get the most from it:

• A comprehensive CFD course, free — a full training course to sharpen your simulation skills, included at no extra cost.

• One month of Claude AI Premium — AI assistance to support your engineering, scripting, and problem-solving.

• One hour of free CFD consultation — direct time with our CFD engineers to help set up, troubleshoot, or optimize your case.

These come standard with the node — practical support alongside the compute.

What this node is built for

GP2 is the flagship GPU, high-memory tier in our lineup. It suits:

• Large GPU-accelerated solves — 96 GB of vRAM lets Fluent's native GPU solver run large supported cases entirely on the card.

• Very large CPU-side meshes — 256 GB of system RAM keeps sizeable steady, transient, and multiphase cases in memory.

• Demanding production CFD — when the case is large and turnaround still matters, flagship GPU acceleration delivers.

• Heavy parameter studies and high-fidelity models — the headroom to run bigger, more detailed simulations than smaller nodes allow.

With the native GPU solver, a large supported case is solved end-to-end on the RTX PRO 6000's 96 GB of vRAM, while 256 GB of system RAM gives the rest of the workflow — meshing, post-processing, and CPU solving — room to breathe.

GPU vs. memory: choosing GP2

GP2's headline is GPU scale — the most vRAM we offer — backed by a large system-memory budget. In CFD, the resources play different roles:

• GPU vRAM (96 GB) sets how large a case the native GPU solver can run on the card. At 96 GB, GP2 handles substantially larger GPU-resident cases than smaller-memory GPUs.

• System RAM (256 GB) sets the largest mesh you can run on the CPU solver — roughly 1 GB of RAM per million cells for a typical steady, single-phase case, so 256 GB supports very large meshes.

• Storage (≈1.9 TB) provides fast datacenter SSD for case files, results, and autosaves.

If your physics is supported by Fluent's GPU solver, GP2's 96 GB of vRAM accelerates cases that simply won't fit on smaller cards. If you're CPU-solving, 256 GB of RAM handles very large meshes. Tell us your cell count, physics, and preferred solver, and we'll confirm GP2 is the right fit.

Fast SSD storage

The two 960 GB datacenter-edition SSDs deliver responsive read/write for loading large case files, writing solution data, and handling autosaves — keeping a fast solve from being held up by slow disk I/O. If your work involves long transient runs that write very large datasets, let us know and we can advise on the right storage configuration for your job.

How GPU-accelerated solving works on this node

Fluent's native GPU solver runs the entire computation on the GPU rather than the CPU. When you launch a supported case, the solver loads your mesh and solution data into the RTX PRO 6000's 96 GB of vRAM and iterates directly on the Blackwell architecture's thousands of parallel cores. Because the data stays resident on the GPU, the solver avoids constant CPU–GPU transfers — and with 96 GB available, even large cases can be held entirely in GPU memory, where smaller cards would run out of room.

For cases not yet covered by the GPU solver, Fluent runs in CPU-parallel mode across the Xeon Gold's 24 cores, partitioning the mesh and exchanging boundary data each iteration via MPI — with 256 GB of RAM keeping very large meshes in memory.

Why rent instead of buy

A flagship 96 GB GPU is a significant purchase to own and maintain. Renting GP2 gives you that top-tier compute on demand — plus a free course, a month of Claude AI Premium, and a consultation hour — without the capital cost or the upkeep.

How it works — you're in full control

GP2 is yours to drive directly. You connect to the node over a secure remote desktop connection and run everything yourself, exactly as you would on a local workstation:

1. Connect via remote desktop — you get full remote access to the GP2 node.

2. Set up your simulation — load your geometry and case, configure your solver settings, and run ANSYS Fluent with GPU or CPU solving at your command.

3. Run and monitor in real time — start, pause, adjust, and watch the solution as it progresses, with complete control throughout.

4. Keep your results — post-process on the node or download your solution and data files whenever you're ready.

You have full authority over the node for the duration of your rental: we provide the hardware and the support, and you run the simulations your way.

Frequently asked questions

What makes GP2 your top GPU node? GP2 carries the most GPU memory in our range — 96 GB of GDDR7 on the RTX PRO 6000 Blackwell Max-Q — paired with 256 GB of system RAM. That combination lets it run large cases on the native GPU solver and very large meshes on the CPU solver, beyond what smaller nodes can handle.

How is GP2 different from GP1? Both are GPU-accelerated nodes. GP1 pairs a 20 GB RTX 4000 Ada GPU with 64 GB of RAM for moderate-to-large work; GP2 steps up to a 96 GB Blackwell GPU and 256 GB of RAM for large-scale, high-fidelity, and memory-hungry cases.

Which cases benefit from the GPU solver? Fluent's native GPU solver supports a growing set of physics. Large cases that fall within its supported models gain the most from GP2's 96 GB of vRAM. If your physics isn't yet supported on GPU, GP2 still runs it on the CPU. Send us your setup and we'll confirm the best path.

How large a mesh can it handle? It depends on the solver. On the GPU solver, the 96 GB of vRAM allows large GPU-resident cases; on the CPU solver, plan around the 256 GB of system RAM (roughly 1 GB per million cells for simpler steady single-phase cases, fewer for transient or multiphase physics). Send us your case for a precise answer.

Is my data kept confidential? Yes. Your geometry, case files, and results stay private to you, treated as strictly confidential — and because you run everything yourself over remote desktop, your work stays under your control throughout.

Get started with GP2

If you need flagship GPU acceleration with the memory to match — plus a free CFD course, a month of Claude AI Premium, and a consultation hour included — GP2's 96 GB Blackwell GPU and 256 GB of RAM are built for your largest, most demanding cases.

Contact MR CFD for remote-desktop access to GP2 — and we'll help you confirm it's the right tier for your simulation.

Two things to flag so your spec sheet stays accurate:

• Memory type: You listed the RAM as DDR4, and I've kept it that way in the table to match your input. Note that the Xeon Gold 5412U (Sapphire Rapids) is a DDR5 platform — so this may be a typo. If it should read DDR5, say the word and I'll correct it throughout.

• Naming: I used GP1 / GP2 to position this as the flagship above the previous GPU node. If your GPU tiers use a different scheme, tell me and I'll rename across both pages and wire up the cross-references (the GP1 page can then point up to GP2, and SC-series pages can reference both).

Want a compact product-grid card version of GP2, or this delivered as a ready-to-paste .md / HTML file?