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Can the RTX 2060 6 GB run FLUX.2 [klein] 4B?

Yes, but only just: FP8 leaves 0.1 GB free on the RTX 2060 6 GB.

Image model · 4B6 GB GDDR6 · 192-bit · 336 GB/s · TuringData 2026-10-01
Runs well
Yes, just.

FP8 (4.1 GB) fits with only 0.1 GB to spare (about 5.9 GB of 6 GB).

Best fileFP8
File size4.1 GB
VRAM needed~5.9 GB
System RAM32 GB+
Memory map · RTX 2060 6 GB5.9 GB / 6 GB
03 GB6 GB
Weights FP8 · 4.1 GBWorking memory · 1.0 GBReserve · 0.8 GBFree · 0.1 GB

01What to download

PartFileFolderSize
Modelflux-2-klein-4b-fp8.safetensors
FP8 · black-forest-labs/FLUX.2-klein-4b-fp8
models/diffusion_models4.1 GBDownload →
Text encoderqwen_3_4b_fp8_mixed.safetensors
Qwen3 4B FP8 · Comfy-Org/z_image_turbo
models/text_encoders5.6 GBDownload →
VAEflux2-vae.safetensors
FLUX.2 VAE · Comfy-Org/flux2-dev
models/vae0.3 GBDownload →
Total download · keep about the same free on disk10.0 GB

Alternatives: Qwen3 4B BF16 (8.0 GB). Sizes from Hugging Face, 2026-10-01.

Free ComfyUI workflow, tested on my RTX 5060 Ti: FP8 workflow (.json). Drag the file into ComfyUI. All workflows →

02Every FLUX.2 klein 4B file on 6 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · black-forest-labs
7.8 GB9.6 GB3.6 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · unsloth
4.3 GB6.1 GBspills 0.1 GBpractically identical to the originalHugging Face →
FP8 ←
SAFETENSORS · black-forest-labs
4.1 GB5.9 GBfits · 0.1 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · unsloth
3.4 GB5.2 GBfits · 0.8 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · unsloth
3.1 GB4.9 GBfits · 1.1 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · unsloth
2.6 GB4.4 GBfits · 1.6 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · unsloth
2.1 GB3.9 GBfits · 2.1 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · unsloth
1.8 GB3.6 GBfits · 2.4 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 1 GB of working memory for FLUX.2 klein 4B and a 0.8 GB reserve. Sizes 2026-10-01.

03The text encoder

At 5.6 GB even the smallest Qwen3 4B file is too big for 6 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. Sizes: 16-bit 8.0 GB, FP8 5.6 GB. Why the encoder does not count against VRAM →

04Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run FLUX.2 klein 4B on a RTX 2060 6 GB, send your time per image and peak VRAM and it will appear here, credited.

05About the RTX 2060 6 GB

The RTX 2060 6 GB (Turing) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain - Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.

6 GB GDDR6 · 192-bit · 336 GB/s · Turing. Everything that runs on it →

06Questions

How much VRAM does FLUX.2 klein 4B need?

Around 3.6 GB with the smallest file (Q2_K) and 5.9 GB with an 8-bit file (FP8). The full 16-bit file needs about 9.6 GB.

Which FLUX.2 klein 4B file should I download for the RTX 2060 6 GB?

FP8 (4.1 GB) from black-forest-labs/FLUX.2-klein-4b-fp8.

FP8 or Q8_0 for FLUX.2 klein 4B on the RTX 2060 6 GB?

Q8_0 (4.3 GB). The RTX 2060 6 GB has no FP8 maths, so FP8 (4.1 GB) only saves memory and is a step further from the original.

How much do I need to download for FLUX.2 klein 4B on the RTX 2060 6 GB?

10.0 GB: flux-2-klein-4b-fp8.safetensors, qwen_3_4b_fp8_mixed.safetensors, flux2-vae.safetensors.