You need at least 12GB VRAM for Flux, and 16GB is what I actually recommend. Anything below 12GB requires aggressive offloading that makes generation painfully slow. The 8GB GPUs that work fine for SD 1.5 cannot handle Flux without serious compromises.
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You are planning to run Flux locally and want to know exactly how much VRAM each workflow requires before buying a GPU. Maybe you already have a card and want to know what Flux workflows it can handle.
VRAM requirements by workflow
| Flux Workflow | VRAM Used | Minimum GPU | Recommended GPU |
|---|---|---|---|
| Flux schnell (1024x1024) | ~12GB | RTX 3060 12GB | RTX 4070 Ti Super |
| Flux dev (1024x1024) | ~12GB | RTX 3060 12GB | RTX 4070 Ti Super |
| Flux dev + LoRA | ~13GB | RTX 4060 Ti 16GB | RTX 4070 Ti Super |
| Flux dev + ControlNet | ~14GB | RTX 4060 Ti 16GB | RTX 5080 |
| Flux dev + CN + IP-Adapter | ~17GB | RTX 4090 | RTX 4090 |
| Flux fine-tuning (LoRA) | ~18GB | RTX 4090 | RTX 5090 |
| Flux dev at 1536x1536 | ~16GB | RTX 4070 Ti Super | RTX 4090 |
| Flux dev at 2048x2048 | ~22GB | RTX 4090 | RTX 5090 |
A note on what these numbers are measuring, because it is the thing most Flux VRAM tables get wrong. FLUX.1-dev is a 12-billion-parameter model published at BF16, and flux1-dev.safetensors is 23.8GB before the text encoders and VAE. flux1-schnell.safetensors is the same 23.8GB, which is why the two share a row above — schnell is distilled to fewer steps, not to less memory. The figures above are therefore not full-precision resident weights — they are what ComfyUI and A1111 actually use on consumer cards, which means an fp8 or quantised checkpoint and offloading parts of the pipeline to system RAM, the approach Black Forest Labs’ own model card points to. Holding the entire BF16 pipeline in VRAM is a 24GB-card proposition. Going below FP8 cuts further: NF4 or Q4 halves it again, to roughly 6GB of weights. Q8 does not — at 8 bits it is the same size as FP8, so it buys precision back rather than memory.
To put your own combination through it — precision, resolution and how many control modules you keep resident — use the VRAM calculator, which works from the same released weight sizes this page quotes.
Why Flux uses more VRAM than SDXL
Flux uses a flow-matching transformer architecture that is fundamentally more memory-hungry than SDXL’s UNet. The model weights alone are larger, and the attention mechanism scales with resolution. At 1024x1024, Flux dev holds about 12GB of state in memory versus 8GB for SDXL. For a comparison of SDXL vs Flux VRAM requirements, see our Stable Diffusion VRAM guide.
This is not something a driver update or optimization will fix. The architecture requires more memory. Period.
Which GPU should you buy?
- Just want to try Flux? An RTX 3060 12GB (~$250 used) runs Flux schnell and basic Flux dev. Slow, but functional.
- Serious Flux user? The RTX 4070 Ti Super (16GB, ~$800) is the sweet spot. It handles dev + LoRA with room to spare. The RTX 5070 Ti does the same job faster, but at ~$1,050 it is a different budget.
- On the RTX 4060 Ti 16GB? It fits Flux Dev comfortably at 16GB — see our RTX 4060 Ti Flux walkthrough for exact VRAM usage and workflow limits.
- ControlNet + advanced workflows? You need 24GB. The RTX 4090 (
$2,200) or a used RTX 3090 ($820) are your options. - Fine-tuning Flux? The RTX 5090 (32GB, ~$4,900) gives you headroom for training without running out of memory.
Common mistakes to avoid
- Assuming 8GB is enough because it works for SD 1.5 — Flux is a different architecture entirely. An RTX 4060 with 8GB cannot run Flux dev without model offloading that makes each image take over a minute.
- Ignoring quantization options — NF4 Flux models reduce VRAM usage dramatically. A 16GB card can sometimes handle workflows that would normally need 24GB with quantized checkpoints. Our best quantization for Stable Diffusion guide covers which precision levels work best for different diffusion models.
- Buying for current Flux only — Flux 2.0 and future flow-matching models will likely need even more VRAM. Buy one tier above your current minimum if your budget allows.
Final verdict
| VRAM Tier | What It Runs | Best GPU |
|---|---|---|
| 12GB | Flux schnell, basic dev | RTX 3060 12GB |
| 16GB | Flux dev + LoRA + ControlNet | RTX 4070 Ti Super |
| 24GB | Everything + high-res + stacking | RTX 4090 |
| 32GB | Fine-tuning + maximum headroom | RTX 5090 |
For the full GPU ranking for Flux, check the best GPU for Flux guide. If you use ComfyUI specifically, the best GPU for ComfyUI article covers workflow-specific recommendations.
16GB is the new baseline for AI image generation. Flux proved that 8GB cards are no longer enough for cutting-edge models, and this trend will only continue.