Wan2.2-T2V-A14B · QuantStack
Wan2.2-T2V-A14B Q4_K_M
This file is exactly 9,650,090,496 bytes — 8.99 GiB / 9.65 GB at an effective 5.403 bits per weight. The nominal rate for Q4_K_M is lower; mixed-precision tensors make the real figure higher, always.
From the file· 1 file(s), summedFrom the file· 1095 tensors parsed
Get it
8.99 GiB · 1 file
llama.cpp
llama-cli -hf QuantStack/Wan2.2-T2V-A14B-GGUF:Q4_K_M
Downloads and runs in one step, resolving the quantization by name.
Hugging Face CLI
hf download QuantStack/Wan2.2-T2V-A14B-GGUF LowNoise/Wan2.2-T2V-A14B-LowNoise-Q4_K_M.gguf
Direct download
Straight from the Hugging Face CDN — we host nothing and earn nothing from this. Verify what you received against the exact byte count above; a size mismatch is the usual cause of a file that will not load.
Size
8.99 GiB
9.65 GB
Effective bpw
5.403
from real bytes ÷ params
Tensors
1095
Header
0.07 MB
GGUF metadata
What this quantization actually contains
per-tensor types, parsed from the GGUF header
F16
694
Q4_K
280
Q6_K
120
F32
1
A quantization label names a mixture, not a uniform precision. Attention and output tensors are routinely kept at higher precision than the label implies, which is exactly why the effective bits-per-weight above exceeds the nominal rate.