OpenGVLab · vision language

InternVL3_5-14B

OpenGVLab/InternVL3_5-14B

InternVL3_5-14B at Q4_K_M is exactly 9,001,749,952 bytes (8.38 GiB / 9.00 GB) — an effective 4.763 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
15.1B
Architecture
qwen3
null layers
Context
native (config.json)
License

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_S4.62 GiB4,963,309,2802.626bartowski
IQ2_M4.96 GiB5,322,938,0802.817bartowski
Q2_K5.36 GiB5,753,980,6403.045bartowski
IQ3_XXS5.53 GiB5,942,662,8803.144bartowski
IQ3_XS5.94 GiB6,375,297,7603.373bartowski
Q2_K_L6.07 GiB6,513,660,6403.446bartowski
Q3_K_S6.20 GiB6,657,102,5603.522bartowski
IQ3_M6.41 GiB6,883,406,5603.642bartowski
Q3_K_M6.82 GiB7,321,309,9203.874bartowski
Q3_K_L7.36 GiB7,900,647,8724.180lmstudio-community
Q3_K_L7.36 GiB7,900,648,1604.180bartowski
IQ4_XS7.55 GiB8,110,726,8804.292bartowski
IQ4_NL7.95 GiB8,541,359,8404.519bartowski
Q4_07.96 GiB8,542,998,2404.520bartowski
Q4_K_S7.98 GiB8,573,472,4804.536bartowski
Q4_K_M8.38 GiB9,001,749,9524.763lmstudio-community
Q4_K_M8.38 GiB9,001,750,2404.763bartowski
Q4_18.74 GiB9,389,518,5604.968bartowski
Q4_K_L8.92 GiB9,579,107,0405.069bartowski
Q5_K_S9.56 GiB10,263,891,6805.431bartowski
Q5_K_M9.79 GiB10,514,566,8805.563bartowski
Q5_K_L10.24 GiB10,994,684,6405.817bartowski
Q6_K11.29 GiB12,121,934,2726.414lmstudio-community
Q6_K11.29 GiB12,121,934,5606.414bartowski
Q6_K_L11.64 GiB12,498,735,8406.613bartowski
Q8_014.62 GiB15,698,530,7528.306lmstudio-community
Q8_014.62 GiB15,698,531,0408.306bartowski
BF1627.51 GiB29,543,420,35215.632bartowski

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 7.92 GiB. The real file is 8.38 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
Attention heads
KV heads
Head dim
Hidden size
Vocab
Sliding window
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does InternVL3_5-14B need?
Q4_K_M is exactly 9,001,749,952 bytes (8.38 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of InternVL3_5-14B 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.