Qwen · image

Qwen-Image-Edit

Qwen/Qwen-Image-Edit

Qwen-Image-Edit at Q4_K_M is exactly 11,738,053,152 bytes (10.93 GiB / 11.74 GB) — an effective 4.596 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
20.4B
Architecture
qwen_image
Context
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q2_K_S6.55 GiB7,029,340,7042.752calcuis
TQ2_06.55 GiB7,031,700,0002.753calcuis
IQ2_S6.55 GiB7,034,206,7522.754calcuis
Q2_K6.58 GiB7,062,518,3042.765QuantStack
Q2_K6.59 GiB7,071,808,0322.769calcuis
Q2_K6.72 GiB7,217,936,9282.826unsloth
Q3_K_S8.34 GiB8,952,609,3123.506QuantStack
IQ3_XXS8.36 GiB8,975,022,6243.514calcuis
IQ3_S8.36 GiB8,979,888,6723.516calcuis
Q3_K_S8.40 GiB9,017,489,9523.531calcuis
Q3_K_S8.42 GiB9,042,852,3843.541unsloth
Q3_K_M8.47 GiB9,092,545,0563.560calcuis
Q3_K_L8.53 GiB9,158,605,3443.586calcuis
Q3_K_M9.01 GiB9,679,567,3923.790QuantStack
Q3_K_M9.08 GiB9,744,742,9443.816unsloth
Q3_K_L9.71 GiB10,428,938,7844.084unsloth
IQ4_XS10.20 GiB10,955,061,7924.290calcuis
IQ4_NL10.80 GiB11,592,071,7124.539calcuis
Q4_K_S10.80 GiB11,596,790,3044.541calcuis
Q4_K_M10.93 GiB11,738,053,1524.596calcuis
Q4_011.04 GiB11,852,773,9204.641QuantStack
Q4_011.04 GiB11,852,773,9204.641unsloth
Q4_K_S11.31 GiB12,140,608,0324.754QuantStack
Q4_K_S11.43 GiB12,268,010,0164.804unsloth
Q4_111.96 GiB12,843,678,2405.029unsloth
Q4_111.96 GiB12,843,678,2405.029QuantStack
Q4_111.98 GiB12,866,091,5525.038calcuis
Q4_K_M12.17 GiB13,065,746,9765.116QuantStack
Q4_K_M12.23 GiB13,127,088,6725.140unsloth
Q5_K_S13.15 GiB14,117,698,0805.528QuantStack
Q5_K_S13.17 GiB14,140,111,3925.537calcuis
Q5_013.17 GiB14,140,111,3925.537calcuis
Q5_K_M13.24 GiB14,215,313,9525.566calcuis
Q5_K_S13.32 GiB14,298,184,2245.599unsloth
Q5_013.41 GiB14,400,813,6005.639unsloth
Q5_013.41 GiB14,400,813,6005.639QuantStack
Q5_K_M13.91 GiB14,934,899,2325.848QuantStack
Q5_K_M13.97 GiB15,000,074,7845.874unsloth
Q5_114.33 GiB15,391,717,9206.027QuantStack
Q5_114.33 GiB15,391,717,9206.027unsloth

Pipeline components

a diffusion model is a graph of parts, not one file
ComponentSizeShareCan live on the CPU?
denoiser38.05 GiB71%no, must be resident
vae0.24 GiB0%no, must be resident
text encoder15.45 GiB29%yes — the usual first VRAM saving
Full pipeline53.74 GiBresident if nothing is offloaded

The parameter count published for a diffusion model describes the denoiser alone. Running it also requires its text encoder and VAE, and the text encoder is often nearly as large as the denoiser — which is why offloading it is the standard first move when you run out of memory.

We publish component sizes here, not throughput. Community-submitted image-generation rates do exist for many GPUs and we show them on the hardware pages, but they aggregate runs at different resolutions, step counts and settings, so they cannot be attributed to one model. Peak memory during sampling is unmeasured by any public source, and we do not estimate it.

Compare with

same modality, comparable size

Will it run on your card?

full quant x context sweep

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 10.70 GiB. The real file is 10.93 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

Architecture unavailable — this repository is gated and no ungated mirror was found. Exact file sizes above are still authoritative; only the KV math needs the config.

Questions people ask

How much VRAM does Qwen-Image-Edit need?
Q4_K_M is exactly 11,738,053,152 bytes (10.93 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Qwen-Image-Edit should I use?
Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.