Qwen-Image 2.1 on 16 GB of VRAM, quantized to NF4: a real benchmark against FLUX

A developer benchmarked Qwen-Image-2.1-Turbo quantized to NF4 against FLUX.1-dev Q6_K with a pixel-art LoRA on a single 16 GB RTX 4070 Ti SUPER, finding Qwen NF4 generated images in 8.4 seconds versus 61 seconds for FLUX at 1344×768 and rendered requested text exactly in 13 of 18 cases versus 7 for FLUX. The writeup also documents failure modes, including an 8-bit LLM.int8 transformer producing a near-uniform purple field and tiled VAE decoding leaving vertical streaks, fixed by decoding the full frame after offloading the transformer and text encoder.

On a 16 GB RTX 4070 Ti SUPER, Qwen-Image-2.1-Turbo does not fit in bf16 the pipeline is 32.5 GB . Quantized to NF4 with bitsandbytes it does, and I ran it against the FLUX.1-dev Q6 K + pixel-art LoRA that made my blog covers: same prompts, same seeds, same card, every image checked by eye. What I measured - Speed: 8.4 s per image for Qwen NF4 8 steps against 61 s for FLUX + LoRA 30 steps , median, 1344×768. About 7×. - Text in the image: 13 of 18 requested texts exact for Qwen NF4, 7 for FLUX. Unquantized Qwen on a 48 GB A6000 got 17. - Cover prompts: Qwen NF4 drew the requested scene in 11 of 15 covers; FLUX + LoRA in none 6 almost, 9 missing the main action or object . - Memory: 11.9 GiB over the card's baseline for Qwen NF4 nvidia-smi , 13.1 GiB for FLUX. What broke on the way - An 8-bit LLM.int8 transformer returns a near-uniform purple field. NF4 works. - Decoding the VAE in tiles needed to fit left faint vertical purple streaks. Fix: make the latents first, drop the transformer and the text encoder from the GPU, then decode the whole frame 0.77 s, 7.1 GiB peak . - An automatic reader gemma3:4b accepted misspelled text, and an external audit caught five of my own verdicts. Every number in the post comes from the corrected image-by-image review. What I lose: the LoRA's atmosphere. Qwen follows the scene but on a flatter background. I switched anyway: every cover on the blog is now generated by Qwen NF4. Read the full measurements, the side-by-side galleries and the code → https://efraingaray.com/en/blog/qwen-image-vs-flux/ https://efraingaray.com/en/blog/qwen-image-vs-flux/ Scripts, prompts and the per-image review: gist https://gist.github.com/EfrainGaray/427b5cc1875b888fd57e32bf8b886527 .