AI image and video generation workstation, built around VRAM.
Diffusion models for images and video keep several large networks in GPU memory at once, along with the image or clip being generated. VRAM decides which models load, how large an image or how long a clip can be generated, and how many jobs run at a time. Our builds run one GeForce RTX 5090 or up to four RTX PRO Blackwell GPUs.
- 32GBRTX 5090 or RTX PRO 4500
- 48–72GBRTX PRO 5000
- 96GBRTX PRO 6000
- Up to 4GPUs, one queue per GPU
Why image and video models need VRAM
A diffusion pipeline keeps several networks in GPU memory: the image or video model itself, one or more text encoders, and the decoder that turns the result into pixels. At 16-bit precision each network takes about 2 bytes per parameter. A 12-billion-parameter image model is about 24GB of weights on its own, and a large text encoder adds several gigabytes more, which is why smaller cards often move parts of the pipeline in and out of system memory between steps.
Video generation raises the working memory again, because the frames of a clip are processed together. Longer clips and higher resolutions are usually the first things to hit the VRAM limit.
Which GPU for which work
32GB: RTX 5090
One 575W GeForce card with 21,760 CUDA cores and 1,792 GB/s of memory bandwidth. Holds a 12B-class image model at 16-bit with room for a text encoder, and runs on a standard 15A circuit.
RTX 5090 AI workstation →48GB and 72GB: RTX PRO 5000
Room for larger video models, higher resolutions, and longer clips, on a 300W two-slot card that runs one, two, or four to a system.
RTX PRO Blackwell workstation →96GB: RTX PRO 6000
24,064 CUDA cores and 96GB of GDDR7 at 1,792 GB/s, so the whole pipeline, including large video models, stays on one card.
Compare with the RTX 5090 →Two or four GPUs
Most image and video tools run one generation on one GPU. With two or four GPUs, each card runs its own queue: several people, several jobs, or batch renders side by side.
Multi-GPU AI workstation →The rest of the system
Model storage
Checkpoints, LoRAs, and output accumulate quickly. Every build boots from a 1TB to 8TB Samsung 9100 PRO PCIe 5.0 NVMe drive, with more NVMe slots and optional 12TB to 28TB enterprise hard drives for archives.
System memory
When a model does not fit entirely in VRAM, tools offload parts of it to system RAM. The AI 5090 offers 64GB to 128GB of DDR5; the AI PRO and AI MAX offer up to 512GB and 1TB of registered ECC DDR5.
Video encoding
The RTX 5090 and the RTX PRO Blackwell cards include hardware AV1 encoding, for exporting generated video without tying up the processor.
Sustained load
Batch renders hold the GPU at full power for hours. Every system is burn-in tested under sustained full load before it ships.
Power and circuit requirements
A single-GPU system, or two RTX PRO 4500 or 5000 cards, runs on a standard 15A, 120V circuit. Two RTX PRO 6000 cards, or any four-GPU configuration, require a dedicated 20A, 110–120V circuit, with a 30A, 220–240V circuit recommended. Four RTX PRO 6000 cards draw approximately 2,850W and require a dedicated 30A, 220–240V circuit. The configurator shows the requirement for every configuration as you build it.
Assembly, burn-in, and delivery
Each system is assembled by hand at our shop in Fairport, NY, by a shop that has built computers for more than thirty years.
Fit and power validated
The configurator checks physical fit, memory, PCIe slots, and power on every selection. The power supply is sized automatically to the GPU count and estimated draw, with a 12V-2x6 cable for every GPU.
Burn-in under load
Every system is stress-tested under sustained full load and firmware-updated before it leaves the bench, so the first long job is not the first test.
Windows 11 Pro installed
Windows 11 Pro is installed and updated before shipment.
Warranty and support
Every build carries a 3-year warranty and lifetime technical support from the shop that built it.
Quoting and payment
The configurator shows a price for every part and an estimated total, including assembly, burn-in, and testing, as the build is configured. GPU and memory pricing changes frequently, so a technician confirms GPU availability and final pricing by email, with lead time, typically within 1-2 business days. There is no cost and no obligation to request a quote.
Payment for AI workstations is by ACH bank transfer; credit cards are not accepted for these systems. An invoice with bank details is issued once the quote is approved. Systems ship across the United States from Fairport, NY, with local pickup available.
Image and video generation hardware questions
How much VRAM do I need for Stable Diffusion or FLUX?
How much VRAM does AI video generation need?
RTX 5090 or RTX PRO 6000 for image generation?
Can several people generate images at once on one workstation?
What circuit does an image generation workstation need?
How is an AI workstation ordered and paid for?
Related AI workstation pages
RTX 5090 AI workstation
One GeForce RTX 5090, 32GB VRAM, Ryzen 9000, standard 15A circuit.
Read →RTX PRO 6000 Blackwell workstation
One or two RTX PRO Blackwell GPUs, up to 192GB VRAM, Threadripper 9000.
Read →Multi-GPU AI workstation
Up to four RTX PRO Blackwell GPUs, up to 384GB VRAM, Threadripper PRO 9000.
Read →Deep learning workstation
Choosing GPUs, CPU cores, memory, and storage for training.
Read →Local LLM workstation guide
How much VRAM a model needs, and which build provides it.
Read →Configure an image and video generation workstation.
Select a build, a GPU, and the GPU count. Total VRAM, estimated power draw, and the circuit requirement update with every selection.
Have an exact parts list or a department spec sheet? Send the whole list. For more than four GPUs or rackmount systems, see AI servers and larger systems.