black-forest-labs · image

FLUX.1-dev

black-forest-labs/FLUX.1-dev

FLUX.1-dev at Q4_K_M is exactly 6,931,817,760 bytes (6.46 GiB / 6.93 GB) — an effective 4.660 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
11.9B
Architecture
flux
Context
native (config.json)
License
other

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q2_K3.75 GiB4,023,690,5282.705unsloth
Q2_K3.76 GiB4,032,341,2802.711lllyasviel
Q2_K3.76 GiB4,032,341,2802.711city96
Q3_K_S4.87 GiB5,225,604,3843.513unsloth
Q3_K_S4.87 GiB5,234,255,1363.518city96
Q3_K_S4.87 GiB5,234,255,1363.518lllyasviel
Q3_K_M5.00 GiB5,368,489,2483.609780unsloth
Q4_06.32 GiB6,791,167,1364.565lllyasviel
Q4_06.32 GiB6,791,167,1364.565city96
Q4_K_S6.33 GiB6,797,337,8884.569unsloth
Q4_06.33 GiB6,797,337,8884.569780unsloth
Q4_K_S6.34 GiB6,805,988,6404.575lllyasviel
Q4_K_S6.34 GiB6,805,988,6404.575city96
Q4_K_M6.46 GiB6,931,817,7604.660780unsloth
Q4_17.01 GiB7,530,806,4325.062lllyasviel
Q4_17.01 GiB7,530,806,4325.062city96
Q4_17.02 GiB7,536,977,1845.066unsloth
Q5_07.70 GiB8,270,445,7285.559lllyasviel
Q5_07.70 GiB8,270,445,7285.559city96
Q5_K_S7.71 GiB8,276,616,4805.564unsloth
Q5_07.71 GiB8,276,616,4805.564unsloth
Q5_K_S7.72 GiB8,285,267,2325.569city96
Q5_K_S7.72 GiB8,285,267,2325.569lllyasviel
Q5_K_M7.84 GiB8,419,501,3445.660780unsloth
Q5_18.39 GiB9,010,085,0246.056city96
Q5_18.39 GiB9,010,085,0246.056lllyasviel
Q5_18.40 GiB9,016,255,7766.061unsloth
Q6_K9.17 GiB9,848,349,9846.620780unsloth
Q6_K9.18 GiB9,857,000,7366.626city96
Q6_K9.18 GiB9,857,000,7366.626lllyasviel
Q8_011.84 GiB12,708,281,5048.542city96
Q8_011.84 GiB12,708,281,5048.542lllyasviel
Q8_011.84 GiB12,714,452,2568.546780unsloth
F1622.17 GiB23,802,870,94416.000lllyasviel
F1622.17 GiB23,802,870,94416.000city96
BF1622.17 GiB23,809,041,69616.004unsloth
F1622.17 GiB23,809,041,69616.004780unsloth

Pipeline components

a diffusion model is a graph of parts, not one file
ComponentSizeShareCan live on the CPU?
text encoder 28.87 GiB28%yes — the usual first VRAM saving
text encoder0.23 GiB1%yes — the usual first VRAM saving
denoiser22.48 GiB71%no, must be resident
vae0.16 GiB0%no, must be resident
Full pipeline31.74 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. This repository also ships a single-file copy of the denoiser at its root; we count it once, not twice.

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.

Measured

published by a third party, attributed below
MetricValueWhat it means
it/s0.3
it/s0.3
it/s0.3
it/s0.3
it/s0.3
it/s0.3
Benchmarked· by vladmandic-sd-data-benchmark

Measured by a third party on their own hardware. We reproduce these figures with attribution; they are not ours and we have not verified the runs. Source: vladmandic-sd-data-benchmark.

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 6.23 GiB. The real file is 6.46 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 FLUX.1-dev need?
Q4_K_M is exactly 6,931,817,760 bytes (6.46 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of FLUX.1-dev 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.