LTX2.3-10Eros · vantagewithai
LTX2.3-10Eros Q3_K_M
This file is exactly 11,130,418,592 bytes — 10.37 GiB / 11.13 GB at an effective 4.239 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· 4444 tensors parsed
Get it
10.37 GiB · 1 file
llama.cpp
llama-cli -hf vantagewithai/LTX2.3-10Eros-GGUF:Q3_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-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.
Size
10.37 GiB
11.13 GB
Effective bpw
4.239
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
Q3_K
1214
Q4_K
324
Q5_K
206
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.