black forest labs

Flux.2 Klein 9B

Frontier

by Black Forest Labs

Mid-range 9B variant of FLUX.2 Klein family. Sub-second generation on H100. DiT architecture with T5-XXL + CLIP-L text encoders (4.82B combined). Higher quality than the 4B sibling while remaining efficient.

VRAM requirements, GPU fit, and setup notes for Flux.2 Klein 9B, including 8GB/12GB fit guidance where relevant. Recommended runtimes: ComfyUI and Diffusers support. Best download size: ~9.0 GB at FP8.

  • 9B DiT — sub-second on H100
  • Higher quality than Klein 4B
  • T5-XXL + CLIP-L text encoders (4.82B)
  • Non-commercial license
HuggingFaceDocumentation
111K downloads566 likes
ComfyUI, DiffusersFP8 safetensors

Your hardware

Detecting...

Parameters9B
Max Resolution1024×1024
Default Steps20
ArchitectureDIT
Licenseflux-2-non-commercial

Image Quality Benchmarks

Measured quality metrics for Flux.2 Klein 9B outputs.

Human Preference Score88%

How often humans prefer this model's output (0-100%)

Aesthetic Score7.8

Visual quality and composition rating (5-9 scale)

VRAM Requirements by Resolution and Precision

Compare which GPUs can run Flux.2 Klein 9B at different precisions. FP8 uses less memory than FP16 when available, and the grade shows how comfortably each GPU handles the workload.

FP16 (full precision)

ResolutionVRAM RequiredRTX 4090 24GBRTX 3060 12GBRTX 4060 8GBMacBook Pro M4 Pro 24GB
512×51228.5 GBDFFF
768×76828.7 GBDFFF
1024×102429.0 GBDFFF

FP8 (~40% less VRAM)

ResolutionVRAM RequiredRTX 4090 24GBRTX 3060 12GBRTX 4060 8GBMacBook Pro M4 Pro 24GB
512×51213.6 GBSBFS
768×76813.8 GBSDFS
1024×102414.0 GBSDFA

Optimization Tips

Turbo / LCM distillation

Use distilled scheduler at 4-8 steps for faster iteration

Run with Python

Run with Python (diffusers)
from diffusers import FluxPipeline
import torch

pipe = FluxPipeline.from_pretrained(
    "black-forest-labs/FLUX.2-klein-9B",
    torch_dtype=torch.float16
)
pipe.to("cuda")

image = pipe(
    prompt="your prompt here",
    num_inference_steps=20,
    guidance_scale=3.5,
    height=1024,
    width=1024,
).images[0]
image.save("output.png")

Get started

Setup instructions for running Flux.2 Klein 9B locally

1. Download the model

Get the checkpoint from HuggingFace

2. Place in:

ComfyUI/models/checkpoints/

3. Launch ComfyUI

python main.py

Memory Breakdown

VRAM allocation at 1024×1024 on RTX 4090 24GB (24 GB)

Required: 29.0 GBAvailable: 24.0 GB
Weights18.0 GB
VAE0.2 GB
Text Encoder9.6 GB
Activations0.6 GB
Overhead0.5 GB

Estimated Generation Time

Time per image at 1024×1024, 28 steps, FP16.

RTX 4090 24GB~3.7s
RTX 3060 12GB~7.6s
RTX 4060 8GB~11.4s
MacBook Pro M4 Pro 24GB~16.2s

Sample Outputs

Available Formats, Downloads & Setup

Download Flux.2 Klein 9B in the precision that matches your GPU. Lower precision usually means less VRAM pressure, while higher precision keeps more quality.

フォーマット精度サイズプロバイダー
safetensors推奨FP1618.0 GBofficialダウンロード
safetensorsFP89.0 GBofficialダウンロード

LoRA Ecosystem

Limited

Limited LoRA availability. Some FLUX.2 LoRAs may be compatible.

Related Workflows

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Frequently asked questions

FAQ — Flux.2 Klein 9B VRAM, Runtimes & Fit

How much VRAM does Flux.2 Klein 9B need?

Flux.2 Klein 9B (9B parameters) requires approximately 29.0 GB of VRAM at FP16 precision for standard 1024×1024 image generation. If you want a lighter setup, lower precisions like FP8 can reduce memory use when available.

Can I run Flux.2 Klein 9B on an 8GB GPU?

Flux.2 Klein 9B usually needs more than 8GB for comfortable local use. Check the VRAM table above for the exact resolution and precision trade-off.

Does Flux.2 Klein 9B work in ComfyUI and Diffusers?

Flux.2 Klein 9B is marked for ComfyUI and Diffusers support in our catalog, so those are the runtimes we recommend first for local setup. If your workflow uses another front end, check the model's available formats and workflow notes above before downloading.

Can I run Flux.2 Klein 9B on RTX 4090?

Flux.2 Klein 9B is too large for the RTX 4090's 24 GB VRAM at FP16. Consider using FP8 precision or a GPU with more VRAM.

Does Flux.2 Klein 9B support ControlNet?

There are currently no known ControlNet adapters for Flux.2 Klein 9B. Check Hugging Face and Civitai for community-contributed adapters.

Does Flux.2 Klein 9B have LoRA support?

Limited LoRA availability. Some FLUX.2 LoRAs may be compatible. The LoRA ecosystem for Flux.2 Klein 9B is rated as "minimal". Each LoRA adds roughly 0.2 GB of extra VRAM.

How fast is Flux.2 Klein 9B?

On a reference GPU (RTX 4090 24GB), Flux.2 Klein 9B generates a 1024×1024 image in approximately ~3.7s at FP16 with 28 inference steps. Faster GPUs with higher memory bandwidth will produce images more quickly.

About Flux.2 Klein 9B

Use cases
photorealisticartdesigntext-rendering
Recommended runtimes
comfyuidiffusers

See also