Cross-posted from Best GPU for AI — visit the original for our VRAM calculator, GPU comparison table, and current Amazon pricing.
You open ComfyUI, load an SDXL checkpoint, add a ControlNet, and hit generate. Ten seconds later your GPU runs out of memory. Sound familiar? SDXL is significantly more demanding than SD 1.5, and choosing the wrong card means constant OOM errors or painfully slow generation. Here is what you actually need.
See the recommended pick on the original guide
Who this is for
This guide covers GPU selection specifically for SDXL workflows — base generation, inpainting, ControlNet, upscaling, and LoRA training. If you are running SD 1.5 or Flux, see our dedicated guides for Stable Diffusion and Flux.
SDXL VRAM requirements
| Workflow | Minimum VRAM | Recommended VRAM |
|---|---|---|
| SDXL base (1024x1024) | 8GB | 12GB |
| SDXL + ControlNet | 10GB | 16GB |
| SDXL + ControlNet + upscaler | 12GB | 16GB |
| SDXL + multiple ControlNets | 14GB | 16-24GB |
| SDXL LoRA training | 10GB | 16GB |
| SDXL Dreambooth | 12GB | 24GB |
The baseline SDXL model uses about 6.5GB of VRAM. Each ControlNet adds 1.5-2.5GB. Upscalers add another 1-2GB. The overhead stacks up fast.
VRAM chart available at the original article
Best GPUs for SDXL ranked
| GPU | VRAM | SDXL (1024px) | SDXL + ControlNet | Price |
|---|---|---|---|---|
| RTX 5090 | 32GB | ~3.5 s/img | ~4.5 s/img | ~$2,000+ |
| RTX 4090 | 24GB | ~5.5 s/img | ~6.5 s/img | ~$1,600 |
| RTX 5070 Ti | 16GB | ~7.0 s/img | ~8.5 s/img | ~$750 |
| RTX 4070 Ti Super | 16GB | ~8.5 s/img | ~10 s/img | ~$700 |
| RTX 4060 Ti 16GB | 16GB | ~12 s/img | ~14 s/img | ~$400 |
| RTX 3060 12GB | 12GB | ~16 s/img | ~19 s/img | ~$250 used |
The 16GB sweet spot
For SDXL, 16GB VRAM is the practical sweet spot. It handles:
- Base SDXL generation at 1024x1024 with headroom
- One ControlNet layer without memory pressure
- Upscaling with Tile ControlNet or ESRGAN
- LoRA training at reasonable batch sizes
Three cards hit this mark at different price points:
RTX 4070 Ti Super (~$700) — Best value for SDXL. Fast generation, 16GB VRAM, and strong compute. The card most SDXL users should buy.
RTX 5070 Ti (~$750) — Slightly faster with GDDR7 bandwidth. Worth the small premium if you generate images frequently.
RTX 4060 Ti 16GB (~$400) — Budget option that still has 16GB. Slower generation but handles the same workflows.
See the recommended pick on the original guide
When you need 24GB or more
If you stack multiple ControlNets, run SDXL at 2K+ resolution, or train Dreambooth models regularly, 16GB gets tight. The RTX 4090 at 24GB eliminates memory concerns entirely and generates images nearly twice as fast as 16GB cards.
See the recommended pick on the original guide
Which GPU should you buy?
Basic SDXL generation with occasional ControlNet: The RTX 4060 Ti 16GB at $400 handles this without issues. Generation is slower but you will not hit OOM.
Regular SDXL work with ControlNet workflows: The RTX 4070 Ti Super at $700 is the sweet spot. Fast enough for iterative creative work, 16GB covers complex pipelines.
Professional SDXL production or Dreambooth training: The RTX 4090 at $1,600 gives you 24GB and top-tier speed. Worth it if image generation is your daily workflow. For trainer-specific picks, our best GPU for Dreambooth guide covers VRAM and batch-size trade-offs in more detail.
Maximum headroom and fastest output: The RTX 5090 at $2,000+ guarantees you never think about VRAM again.
Common mistakes to avoid
- Buying an 8GB card for SDXL. It technically works for base generation, but any ControlNet or upscaler pushes you over the edge. 12GB is the real minimum, 16GB is recommended.
- Running SDXL at FP32 precision. Always use FP16 or BF16. FP32 doubles VRAM usage for zero visible quality improvement in generated images.
- Ignoring VAE tiling for high-res work. If you upscale or generate above 1024px, enable VAE tiling to avoid OOM during the decode step. For dedicated upscaler workloads beyond SDXL's hires-fix, see our best GPU for AI upscaling guide.
- Choosing raw compute over VRAM. A faster card with 8GB is worse for SDXL than a slower card with 16GB. VRAM determines what you can run; speed determines how fast.
Final verdict
| Budget | GPU | Why |
|---|---|---|
| $250 | RTX 3060 12GB (used) | Minimum viable SDXL card |
| $400 | RTX 4060 Ti 16GB | Budget 16GB for SDXL |
| $700 | RTX 4070 Ti Super | Best value for SDXL |
| $1,600 | RTX 4090 | Power user + training |
See the recommended pick on the original guide
See the recommended pick on the original guide
For most SDXL users, a 16GB card is the right call. The RTX 4070 Ti Super delivers the best balance of speed, VRAM, and price. Check our full guides on Stable Diffusion GPUs and Flux GPUs for broader comparisons.
SDXL eats VRAM for breakfast. Buy 16GB minimum, and you will never fight OOM errors again.
Related guides on Best GPU for AI
- How Much VRAM Do You Need for Stable Diffusion in 2026?
- Best GPU for AI Art in 2026: Every Budget Compared
- Best GPU for Stable Diffusion 2026: 7 Picks ($249-$1,999)
The full version lives on Best GPU for AI — VRAM calculator, GPU comparison table, and live Amazon pricing.
