AI Image Generator

FLUX.1 [dev]

Guidance-distilled 12B open-weight image generation model powering the ComfyUI, LoRA, ControlNet, and FP8/GGUF local ecosystem.

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FLUX.1 [dev]
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GPU VRAM اور کوانٹائزیشن کیلکولیٹر

FLUX.1 [dev] GPU VRAM اور ہارڈویئر مطابقت کیلکولیٹر

Calculate required VRAM (model weights + activation/KV cache) across BF16, FP8, INT4, and GGUF Q4_K_M.

Quantization Precision
Context / Image Resolution
Estimated Required VRAM
17.4 GB FLUX.1 Non-Commercial (Commercial via API)
Model Weights: 15.2 GB KV / Activation Overhead: 2.2 GB

Instant Hardware Compatibility

RTX 3060 12GB Insufficient VRAM
RTX 4070/4080 16GB CPU Offload / Tight
RTX 4090 24GB Smooth Fit
Mac Apple Silicon 16GB/32GB/64GB Needs 32GB+ Unified
Cloud GPU / API Cloud / API Ready

FLUX.1 Pro vs Dev vs Schnell Comparison

Model Variant License Speed / Steps Local vs API Commercial Use
FLUX 1.1 [pro] / [pro] Proprietary Cloud API ~4s Ultra-Fast (Up to 4MP Ultra) Cloud API Only ($0.04–$0.06/img · 0 GB Local) Yes — Full Commercial Rights
FLUX.1 [dev] (12B) FLUX.1 Non-Commercial Weights 20–50 Guidance Steps (Best LoRA Fidelity) Local GPU (12–24 GB in NF4/FP8) + Cloud API Non-Commercial Local (Commercial via Official API)
FLUX.1 [schnell] (12B) Apache 2.0 Open Source 1–4 Timestep Distilled (~1.5s Local) Local GPU (12 GB+ in NF4/GGUF/FP8) + API Yes — Free Commercial & Self-Hosted Use

اس ٹول کے بارے میں

FLUX.1 [dev] is the 12-billion-parameter guidance-distilled open-weight checkpoint from Black Forest Labs that anchors local AI art workflows in ComfyUI, Stable Diffusion WebUI Forge, and Diffusers.

Local GPU VRAM & Quantization Guide

  • 24 GB GPUs (RTX 3090 / 4090): Run fp8_e4m3fn (~17.4 GB total VRAM) at full 1024×1024 speed with headroom for ControlNet and LoRA stacks.
  • 12 GB–16 GB GPUs (RTX 3060 / 4060 Ti / 4070): Use NF4 or GGUF Q4_K_M / Q5_K_M quantized weights (~11.5–12.5 GB) for smooth local generation.
  • Licensing: Local self-hosted weights carry the FLUX.1 Non-Commercial License; use Apache 2.0 FLUX.1 [schnell] or licensed cloud APIs for commercial deliverables.
#FLUX.1 Dev, ComfyUI, LoRA Training, FP8 GGUF VRAM

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FLUX.1 [dev]

اکثر پوچھے گئے سوالات

What GPU VRAM is recommended for FLUX.1 [dev] 12B in ComfyUI?

For zero-compromise speed without CPU offloading, an RTX 4090 (24GB) or Mac with 32GB+ unified memory runs FLUX.1 [dev] FP8 (~17.4 GB VRAM) effortlessly. On 12GB–16GB GPUs (RTX 3060 / 4070), use GGUF Q4_K_M or NF4 weights (~11.1–11.7 GB) or ComfyUI weight offloading.

How many sampling steps and CFG settings work best for FLUX.1 [dev]?

FLUX.1 [dev] uses guidance distillation: set standard CFG to 1.0 and FluxGuidance between 3.0 and 3.5 with 20 to 28 steps (Euler + Simple/Beta scheduler) for crisp textures and accurate prompt following.

Why do LoRA creators prefer FLUX.1 [dev] over FLUX.1 [schnell]?

Because FLUX.1 [dev] retains multi-step guidance dynamics rather than 4-step timestep distillation, character, product, and style LoRAs train with far higher anatomical stability and fine detail retention.

Is FLUX.1 [dev] free for commercial client work?

Self-hosted FLUX.1 [dev] weights are governed by the FLUX.1 Non-Commercial License. For commercial client deliverables without buying an enterprise self-hosting license, either run FLUX.1 [schnell] (Apache 2.0) or call a commercially licensed hosted FLUX.1 [dev]/[pro] API.

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