SulphurAI · video

Sulphur-2-base

SulphurAI/Sulphur-2-base

Sulphur-2-base at Q4_K_M is exactly 5,629,108,608 bytes (5.24 GiB / 5.63 GB) — an effective 4.896 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
9.2B
Architecture
ltxv
Context
native (config.json)
License

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ4_NL5.07 GiB5,443,379,5844.735PeppX
Q4_K_M5.24 GiB5,629,108,6084.896427PeppX
Q3_K_S9.63 GiB10,339,464,5638.994Abiray
Q3_K_M10.37 GiB11,130,418,5279.6824444Abiray
Q4_012.09 GiB12,980,918,64111.2914444Abiray
Q4_K_S12.29 GiB13,201,119,60311.483Abiray
Q4_K_M13.22 GiB14,194,463,07212.347coolthor
Q4_K_M13.31 GiB14,296,160,60712.4354444Abiray
Q5_K_S14.01 GiB15,043,615,09113.085Abiray
Q5_014.21 GiB15,261,718,89713.275Abiray
Q5_K_M15.03 GiB16,141,485,40714.0404444Abiray
Q6_K16.55 GiB17,774,930,27115.4614444Abiray
Q8_021.19 GiB22,755,563,87119.7944444Abiray

Pipeline components

a diffusion model is a graph of parts, not one file
ComponentSizeShareCan live on the CPU?
denoiser122.66 GiB100%no, must be resident
Full pipeline122.66 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 4.82 GiB. The real file is 5.24 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 Sulphur-2-base need?
Q4_K_M is exactly 5,629,108,608 bytes (5.24 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Sulphur-2-base 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.