FLUX.1 Dev VRAM Requirements
How much VRAM FLUX.1 Dev needs for local image generation — from full FP16 on a 24 GB GPU to quantized workflows on 12–16 GB cards.
FLUX.1 Dev VRAM Requirements
FLUX.1 Dev is the guidance-distilled sibling of FLUX.1 Schnell — slower per step, higher prompt adherence, and heavier on VRAM. Same 12B parameter architecture, but the recommended headroom is higher.
Requirements at a glance
| Precision | Minimum VRAM | Comfortable VRAM | Notes |
|---|---|---|---|
| FP16 full precision | 24 GB | 24 GB+ | Hard floor for high-res without offload |
| FP8 mixed precision | 16 GB | 16 GB | Good balance of quality and speed |
| NF4 / INT8 quantized | 12 GB | 16 GB | Works, but slower and lower throughput |
| CPU offload | 8 GB | — | Testing only |
System RAM: 32 GB minimum regardless of precision. Model loading and VAE operations pull from system memory during pipeline initialization.
FP16 — full precision
- Required VRAM: 24 GB
- GPUs: RTX 3090 24GB, RTX 4090 24GB
- This is the baseline for production-quality workflows — high-res outputs (1024×1024 and above), larger batch sizes, and ControlNet-style extensions all need the full 24 GB buffer.
- Below 24 GB at FP16, you will hit OOM errors on anything beyond the smallest canvas sizes.
FP8 — mixed precision
- Required VRAM: 16 GB
- GPUs: RTX 4080 16GB, RTX 4060 Ti 16GB
- FP8 inference with Diffusers or ComfyUI's built-in quantization keeps quality close to FP16 while fitting on a 16 GB card.
- Expect roughly 10–20% slower generation vs. FP16 on a 24 GB card, mostly due to dequantization overhead.
NF4 / INT8 — quantized
- Required VRAM: 12 GB
- GPUs: RTX 4070 Ti Super 16GB, RTX 4070 12GB, RTX 3060 12GB
- Viable for experimentation and low-volume generation. Not ideal for iterative workflows where you're generating dozens of images.
- Generation speed takes a notable hit at 12 GB — plan for longer wait times per image compared to the 24 GB FP16 path.
- High-resolution outputs (1280×1280+) will likely require resolution compromises or tiled generation.
FLUX.1 Dev vs Schnell — VRAM difference
Both models share the same 12B parameter count, so raw weight size is identical. The VRAM gap comes from workflow differences:
- Dev typically runs more steps (20–50 vs. Schnell's 1–4), which means more intermediate activations in memory simultaneously.
- Dev workflows often include guidance embedding, which adds a small but consistent overhead.
- In practice: if FLUX.1 Schnell runs smoothly on your GPU, Dev will work too — but expect tighter margins and slower generation.
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