Rent NVIDIA RTX PRO 6000 Max-Q GPU by the hour
The NVIDIA RTX PRO 6000 Max-Q is a Blackwell architecture workstation GPU equipped with 96 GB of VRAM and a 300 W power envelope. It delivers about 119.0 TFLOPS of single-precision compute and about 1404 GB/s of memory bandwidth. Rent this GPU on ONIE with per-hour billing, full SSH access, and ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI.
Specifications
VRAM per GPU
Architecture
Compute capability
FP32 compute
Memory bandwidth
Power limit
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Available configurations
Live stock and prices, updated continuously. The final price is confirmed before you order.
Loading live prices…
What the RTX PRO 6000 Max-Q is good for
Large Language Model Inference
Run large language models and long-context workloads entirely within the 96 GB VRAM buffer using pre-configured vLLM or Ollama templates.
Model Fine-Tuning and Training
Utilize compute capability 12.0 and about 119.0 TFLOPS of compute for custom model training and fine-tuning in PyTorch/CUDA.
High-Resolution Generative Media
Execute complex ComfyUI pipelines, multi-model workflows, and large batch generation without encountering memory bottlenecks.
Workstation Rendering and Simulation
Process heavy geometry, high-resolution textures, and scientific simulations backed by about 1404 GB/s of memory bandwidth.
Is it the right GPU for you?
Choose the RTX PRO 6000 Max-Q when your workloads require 96 GB of VRAM and the Blackwell feature set on a single workstation card. Opt for a smaller consumer GPU if your models require less memory, or select a datacenter GPU if your workflow requires higher memory bandwidth than about 1404 GB/s.
Compare with similar GPUs
Frequently asked questions
Is the RTX PRO 6000 Max-Q suitable for LLM inference and fine-tuning?
Yes, its 96 GB of VRAM accommodates substantial model weights and large context windows without offloading to system memory. You can deploy inference servers immediately on ONIE using the vLLM or Ollama templates, or run fine-tuning jobs via the PyTorch/CUDA template.
What does the Max-Q designation mean for this workstation GPU?
The Max-Q design configures this Blackwell workstation GPU to operate within a 300 W thermal design power limit. Even within this power envelope, it provides full access to 96 GB of VRAM, compute capability 12.0, and about 119.0 TFLOPS of single-precision performance.
How does this GPU compare to smaller workstation or larger datacenter cards?
With 96 GB of VRAM and compute capability 12.0, it offers more memory capacity than lower-tier workstation and consumer GPUs, allowing larger batch sizes and models. Compared to high-end datacenter GPUs, it operates at a lower 300 W power rating and has about 1404 GB/s of memory bandwidth.
How do billing and access work on ONIE?
Instances are billed on a per-hour basis while active. You can connect directly to your environment via SSH or launch pre-built templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI.
Rent the RTX PRO 6000 Max-Q by the hour
Create an account, choose a configuration and connect over SSH. Billing stops when you delete the GPU.
Rent RTX PRO 6000 Max-Q