GPUs for image and video generation
Diffusion models generate images and video step by step, each step running the full network. Recent image models need 12 to 24 GB of memory at full resolution; video models and training of custom styles need much more.
GPUs that fit image and video generation
Swipe sideways to see every column.
| GPU | Memory | Memory type | Bandwidth | FP16 tensor | Price/h |
|---|---|---|---|---|---|
| RTX 3090Ampere | 24 GB | GDDR6X | 936 GB/s | Not published | from $0.22 |
| RTX 4090Ada Lovelace | 24 GB | GDDR6X | 1,008 GB/s | Not published | from $0.33 |
| RTX 5090Blackwell | 32 GB | GDDR7 | 1,792 GB/s | Not published | from $0.69 |
| L40SAda Lovelace | 48 GB | GDDR6 | 864 GB/s | 362 TFLOPS | from $0.79 |
| RTX 6000 AdaAda Lovelace | 48 GB | GDDR6 | 960 GB/s | Not published | from $0.74 |
| RTX PRO 6000 BlackwellBlackwell | 96 GB | GDDR7 | 1,792 GB/s | Not published | from $1.69 |
| A100 SXMAmpere | 80 GB | HBM2e | 2,039 GB/s | 312 TFLOPS | from $1.79 |
| H100 SXMHopper | 80 GB | HBM3 | 3,350 GB/s | 989 TFLOPS | from $2.88 |
Manufacturer specifications, per GPU; tensor throughput without sparsity. Model sizes are cautious estimates in billions of parameters, counting 80% of memory; context length, batch size and framework change the real limit. Prices are the best live offer for one GPU per hour, excluding tax.
All GPU modelsWhat matters for image and video generation
Memory for resolution and length
Memory use grows with resolution, batch size and, for video, the number of frames. A 24 GB card runs most image models at full resolution; video generation and large image models are far more comfortable on 48 GB to 96 GB GPUs.
Speed per image
Each denoising step is compute heavy. Newer architectures and higher tensor throughput shorten the time per image; for many images, several GPUs in parallel scale almost linearly.
Training styles and characters
Training LoRA adapters for a diffusion model fits on a 24 GB card; full fine-tuning of a large image model or a video model needs 48 GB or more per GPU.
Compare GPUs for image and video generation
GPUs for image and video generation: frequently asked questions
How much VRAM do I need for Stable Diffusion or Flux?
Recent image models run comfortably with 16 to 24 GB at their native resolution; memory-saving options let smaller cards run them more slowly. Video diffusion models often need 48 GB or more.
RTX 4090 or RTX 5090 for image generation?
The RTX 5090 has 32 GB of GDDR7 memory and about 1.8 TB/s of bandwidth, against 24 GB and about 1 TB/s for the RTX 4090: larger models and batches fit, and generation is faster.
Can I generate images on a data center GPU?
Yes. A100, H100 and L40S GPUs run diffusion models well; they make most sense for large batches, video models or training, where their memory is put to use.
How do I rent a GPU for image and video generation on EverXCloud?
Create an account, top up your prepaid balance in euros, US dollars or pounds, then buy GPU hours on the spot exchange at the best offer, or place a request at the price you are willing to pay. Rentals are billed by the hour. Prices are shown excluding tax and EverXCloud is the merchant of record for every rental.
Plan your GPU rental
- GPU rental: how to rent a cloud GPU by the hour
- How to rent your first GPU
- How to choose a GPU for LLM inference
- How to estimate a GPU rental session
- H100 price per hour: what sets the rate
- How a GPU spot exchange works
- H200 price per hour: cloud pricing explained
- B200 price per hour: B200, B300 and GB200
- A100 price per hour: rent an NVIDIA A100
- RTX 4090 price per hour: rental guide
- RTX 5090 price per hour: rental guide
- L40S price per hour: rental guide
- MI300X price per hour: rental guide
- How much VRAM do you need for an LLM?
- Best GPU for Stable Diffusion and Flux
- Cheapest way to rent a GPU for AI
- Best GPU for scientific computing (FP64)
Check the workload, complete configuration and billing conditions before choosing a live offer.
Be ready on launch day
Create your account now: you can top up your balance and rent the GPU that fits your workload as soon as the market opens.
Have GPU servers?
Businesses can join the EverXCloud Network and sell hours of their GPU servers on the spot exchange.
Other workloads
- GPUs for training large language models
Pre-training and full fine-tuning on data center GPUs with HBM memory.
- GPUs for fine-tuning open models
LoRA and QLoRA adapters on a single GPU, from 24 GB up.
- GPUs for LLM inference
Serve open models: what fits in memory, and how fast tokens come.
- GPUs for 3D rendering and visual effects
Ray-traced rendering, visual effects and real-time engines.
- GPUs for scientific computing and simulation
Simulation and HPC codes on data center GPUs with HBM memory.