HiDream-ai · image

HiDream-I1-Full

HiDream-ai/HiDream-I1-Full

HiDream-I1-Full at Q4_K_M is exactly 11,481,430,592 bytes (10.69 GiB / 11.48 GB) — an effective 5.370 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
17.1B
Architecture
pig
Context
native (config.json)
License
mit

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q2_K6.11 GiB6,562,298,4323.069city96
Q3_K_S7.65 GiB8,211,921,4723.841city96
Q3_K_M8.16 GiB8,765,045,3124.099city96
Q4_09.92 GiB10,650,761,7924.981city96
Q4_K_S10.15 GiB10,893,900,3525.095city96
IQ4_XS10.24 GiB10,990,929,6005.140calcuis
Q4_110.66 GiB11,445,713,4725.353city96
Q4_K_M10.69 GiB11,481,430,5925.370city96
IQ4_NL10.72 GiB11,508,336,3205.382calcuis
Q5_K_S11.62 GiB12,480,526,9125.837city96
Q5_011.85 GiB12,720,388,6725.949city96
Q5_K_M12.14 GiB13,032,012,3526.095city96
Q5_112.59 GiB13,515,340,3526.321city96
Q6_K13.67 GiB14,679,505,4726.865city96
Q8_017.41 GiB18,689,407,5528.741city96
Q2_K5 shards30.47 GiB32,720,936,60815.303calcuis
F1631.86 GiB34,211,609,15216.000city96
Q3_K_S5 shards42.33 GiB45,449,352,51221.256calcuis
Q3_K_M5 shards44.90 GiB48,214,971,71222.549calcuis
Q3_K_L5 shards47.31 GiB50,802,005,31223.759calcuis
Q5_K_S4 shards49.56 GiB53,214,416,51224.887calcuis
Q5_K_M4 shards51.61 GiB55,420,358,27225.919calcuis
Q4_K_S5 shards54.82 GiB58,859,246,91227.527calcuis
Q4_K_M5 shards57.55 GiB61,796,898,11228.901calcuis
Q4_16 shards60.24 GiB64,677,700,48030.248calcuis
Q4_06 shards64.63 GiB69,391,752,19232.453calcuis
Q5_15 shards67.02 GiB71,966,446,912calcuis
Q6_K5 shards72.45 GiB77,787,272,512calcuis
Q5_06 shards76.19 GiB81,809,513,472calcuis
Q8_06 shards109.55 GiB117,623,626,752calcuis
F3213 shards254.90 GiB273,692,302,080calcuis

Pipeline components

a diffusion model is a graph of parts, not one file
ComponentSizeShareCan live on the CPU?
text encoder 38.87 GiB20%yes — the usual first VRAM saving
text encoder0.46 GiB1%yes — the usual first VRAM saving
denoiser31.86 GiB73%no, must be resident
text encoder 22.59 GiB6%yes — the usual first VRAM saving
vae0.16 GiB0%no, must be resident
Full pipeline43.94 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 8.96 GiB. The real file is 10.69 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 HiDream-I1-Full need?
Q4_K_M is exactly 11,481,430,592 bytes (10.69 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of HiDream-I1-Full 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.