GPUs for 3D rendering and visual effects
GPU renderers trace rays on dedicated ray-tracing cores and keep the whole scene, with its textures and geometry, in GPU memory. The scene must fit: memory size first, then ray-tracing generation and clock speed decide the render time.
GPUs that fit 3D rendering
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| GPU | Memory | Memory type | Bandwidth | Max power | Price/h |
|---|---|---|---|---|---|
| RTX 4090Ada Lovelace | 24 GB | GDDR6X | 1,008 GB/s | 450 W | from $0.33 |
| RTX 5090Blackwell | 32 GB | GDDR7 | 1,792 GB/s | 575 W | from $0.69 |
| RTX A6000Ampere | 48 GB | GDDR6 | 768 GB/s | 300 W | from $0.33 |
| A40Ampere | 48 GB | GDDR6 | 696 GB/s | 300 W | from $0.35 |
| L40Ada Lovelace | 48 GB | GDDR6 | 864 GB/s | 300 W | from $0.69 |
| L40SAda Lovelace | 48 GB | GDDR6 | 864 GB/s | 350 W | from $0.79 |
| RTX 6000 AdaAda Lovelace | 48 GB | GDDR6 | 960 GB/s | 300 W | from $0.74 |
| RTX PRO 6000 BlackwellBlackwell | 96 GB | GDDR7 | 1,792 GB/s | Not published | from $1.69 |
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 3D rendering
The scene must fit in memory
Most GPU renderers need the full scene in GPU memory; a scene that does not fit falls back to slower out-of-core modes or fails. Large production scenes are the reason 48 GB and 96 GB workstation GPUs exist.
Ray-tracing cores
Only GPUs with ray-tracing cores are listed here. Each generation (Ampere, Ada Lovelace, Blackwell) speeds up ray traversal; data center GPUs such as the H100 and A100 have no ray-tracing cores and are not meant for rendering.
Frames in parallel
Animation renders frame by frame: several GPUs, or several servers, render different frames at the same time and scale almost linearly. Renting by the hour turns a long render into a short one.
Compare GPUs for 3D rendering
GPUs for 3D rendering and visual effects: frequently asked questions
Which GPU is best for Blender Cycles?
Cycles uses ray-tracing cores through OptiX on NVIDIA RTX GPUs. GeForce RTX 4090 and RTX 5090 cards are fast for scenes that fit in 24 or 32 GB; RTX 6000 Ada and RTX PRO 6000 suit heavier scenes with 48 GB and 96 GB.
Workstation or GeForce card for rendering?
GeForce cards give a lot of speed per GPU with 24 to 32 GB of memory. Workstation cards add memory (48 to 96 GB), ECC on most models and drivers certified for professional applications.
Can I render on an A100 or H100?
They have no ray-tracing cores, so GPU renderers either run without hardware ray tracing or do not support them. Choose an RTX workstation, L40, L40S or GeForce RTX GPU for rendering.
How do I rent a GPU for 3D rendering 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 image and video generation
Diffusion models for images and video, from 24 GB cards to 80 GB GPUs.
- GPUs for scientific computing and simulation
Simulation and HPC codes on data center GPUs with HBM memory.