LGAI-EXAONE · text

EXAONE-3.5-2.4B-Instruct

LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct

EXAONE-3.5-2.4B-Instruct at Q4_K_M is exactly 1,644,918,560 bytes (1.53 GiB / 1.64 GB) — an effective 5.471 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
2.4B
Architecture
exaone
null layers
Context
32,768
native (config.json)
License
other

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M0.95 GiB1,023,555,6163.404bartowski
Q2_K1.02 GiB1,096,459,2963.647bartowski
IQ3_XS1.13 GiB1,208,776,7364.020bartowski
Q3_K_S1.17 GiB1,253,336,0964.168bartowski
IQ3_M1.20 GiB1,293,287,4564.301bartowski
Q2_K_L1.26 GiB1,352,459,2964.498bartowski
Q3_K_M1.27 GiB1,361,793,0564.529bartowski
Q3_K_L1.36 GiB1,458,622,2404.851lmstudio-community
Q3_K_L1.36 GiB1,458,622,4964.851bartowski
IQ4_XS1.40 GiB1,505,291,2965.006bartowski
Q4_01.47 GiB1,576,213,5365.242bartowski
IQ4_NL1.47 GiB1,578,916,8965.251bartowski
Q4_K_S1.47 GiB1,580,473,3765.257bartowski
Q4_K_M1.53 GiB1,644,918,5605.471lmstudio-community
Q4_K_M1.53 GiB1,644,918,8165.471bartowski
Q4_K_L1.71 GiB1,839,478,8166.118bartowski
Q5_K_S1.74 GiB1,873,419,2966.231bartowski
Q5_K_M1.78 GiB1,910,585,3766.354bartowski
Q5_K_L1.93 GiB2,072,377,3766.893bartowski
Q6_K2.04 GiB2,192,855,8407.293lmstudio-community
Q6_K2.04 GiB2,192,856,0967.293bartowski
Q6_K_L2.16 GiB2,319,832,0967.716bartowski
Q8_02.64 GiB2,838,846,2409.442lmstudio-community
Q8_02.64 GiB2,838,846,4969.442bartowski
F164.97 GiB5,339,454,49617.759bartowski
F329.94 GiB10,674,084,640bartowski

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 1.26 GiB. The real file is 1.53 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
Attention heads
32
KV heads
8
Head dim
80
Hidden size
2560
Vocab
102,400
Sliding window
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does EXAONE-3.5-2.4B-Instruct need?
Q4_K_M is exactly 1,644,918,560 bytes (1.53 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of EXAONE-3.5-2.4B-Instruct 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.