LTX2.3-10Eros · vantagewithai
LTX2.3-10Eros Q4_K_M
This file is exactly 14,296,160,672 bytes — 13.31 GiB / 14.30 GB at an effective 5.445 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· 4444 tensors parsed
Get it
13.31 GiB · 1 file
llama.cpp
llama-cli -hf vantagewithai/LTX2.3-10Eros-GGUF:Q4_K_M
Downloads and runs in one step, resolving the quantization by name.
Hugging Face CLI
hf download vantagewithai/LTX2.3-10Eros-GGUF 10Eros_v1-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
13.31 GiB
14.30 GB
Effective bpw
5.445
from real bytes ÷ params
Tensors
4444
Header
0.40 MB
GGUF metadata
What this quantization actually contains
per-tensor types, parsed from the GGUF header
F32
2672
Q4_K
1214
Q6_K
326
Q5_K
204
BF16
28
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.