Wan2.2-VACE-Fun-A14B · QuantStack

Wan2.2-VACE-Fun-A14B Q3_K_M

This file is exactly 8,636,061,600 bytes — 8.04 GiB / 8.64 GB at an effective 3.985 bits per weight. The nominal rate for Q3_K_M is lower; mixed-precision tensors make the real figure higher, always.

From the file· 1 file(s), summedFrom the file· 1331 tensors parsed

Get it

8.04 GiB · 1 file
llama.cpp
llama-cli -hf QuantStack/Wan2.2-VACE-Fun-A14B-GGUF:Q3_K_M

Downloads and runs in one step, resolving the quantization by name.

Hugging Face CLI
hf download QuantStack/Wan2.2-VACE-Fun-A14B-GGUF LowNoise/Wan2.2-VACE-Fun-A14B-low-noise-Q3_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.

Repository →
Size
8.04 GiB
8.64 GB
Effective bpw
3.985
from real bytes ÷ params
Tensors
1331
Header
0.08 MB
GGUF metadata

What this quantization actually contains

per-tensor types, parsed from the GGUF header
F32
836
Q3_K
345
Q4_K
142
BF16
6
Q5_K
2

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.