stabilityai · image

stable-diffusion-3-medium

stabilityai/stable-diffusion-3-medium

stable-diffusion-3-medium at Q4_K_M is exactly 1,326,251,584 bytes (1.24 GiB / 1.33 GB) — an effective 1.346 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
7.9B
Architecture
Context
native (config.json)
License
other

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q4_01.20 GiB1,283,784,2561.303city96
Q4_K_S1.20 GiB1,283,784,2561.303city96
Q4_K_M1.24 GiB1,326,251,5841.346city96
Q4_11.31 GiB1,409,269,3121.431city96
Q5_K_S1.43 GiB1,534,754,3681.558city96
Q5_01.43 GiB1,534,754,3681.558city96
Q5_K_M1.47 GiB1,579,875,9041.604city96
Q5_11.55 GiB1,660,239,4241.685city96
Q6_K1.68 GiB1,801,410,1121.829city96
Q8_02.13 GiB2,287,664,7042.322city96
F163.88 GiB4,169,940,5444.233city96
Q4_04.24 GiB4,553,447,5524.623second-state
Q4_14.69 GiB5,040,724,4165.117second-state
Q5_05.15 GiB5,528,015,2325.612second-state
Q5_15.60 GiB6,015,292,0966.107second-state
Q8_07.87 GiB8,451,720,5768.580second-state
F1614.68 GiB15,760,974,59216.000second-state
F3229.36 GiB31,521,770,68832.000second-state

Pipeline components

a diffusion model is a graph of parts, not one file
ComponentSizeShareCan live on the CPU?
denoiser34.40 GiB100%no, must be resident
Full pipeline34.40 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 4.13 GiB. The real file is 1.24 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 stable-diffusion-3-medium need?
Q4_K_M is exactly 1,326,251,584 bytes (1.24 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of stable-diffusion-3-medium 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.