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Qwen3-4B-abliterated

mlabonne/Qwen3-4B-abliterated

Qwen3-4B-abliterated at Q4_K_M is exactly 2,497,280,544 bytes (2.33 GiB / 2.50 GB) — an effective 4.967 bits per weight, not the nominal 4. Its KV cache at 32K is 4.50 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
4.0B
Architecture
qwen3
36 layers
Context
40,960
native (config.json)
License

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M1.41 GiB1,512,983,5843.009bartowski
Q2_K1.55 GiB1,669,499,4243.320bartowski
Q2_K1.55 GiB1,669,499,5843.320mradermacher
IQ3_XXS1.56 GiB1,670,188,0643.322bartowski
Q2_K_L1.64 GiB1,763,699,7443.508bartowski
IQ3_XS1.69 GiB1,814,374,9443.608bartowski
Q3_K_S1.76 GiB1,886,997,0243.753bartowski
Q3_K_S1.76 GiB1,886,997,1843.753mradermacher
IQ3_M1.83 GiB1,962,895,9043.904bartowski
Q3_K_M1.93 GiB2,075,617,8244.128bartowski
Q3_K_M1.93 GiB2,075,617,9844.128mradermacher
Q3_K_L2.09 GiB2,239,785,5044.455bartowski
Q3_K_L2.09 GiB2,239,785,6644.455mradermacher
IQ4_XS2.11 GiB2,270,751,2644.516bartowski
IQ4_XS2.13 GiB2,286,316,2244.547mradermacher
Q4_02.21 GiB2,375,772,7044.725bartowski
IQ4_NL2.22 GiB2,381,343,2644.736bartowski
Q4_K_S2.22 GiB2,383,309,3444.740bartowski
Q4_K_S2.22 GiB2,383,309,5044.740mradermacher
Q4_K_M2.33 GiB2,497,280,5444.967bartowski
Q4_K_M2.33 GiB2,497,280,7044.967mradermacher
Q4_K_L2.41 GiB2,591,480,8645.154bartowski
Q4_12.42 GiB2,596,629,0245.164bartowski
Q5_K_S2.63 GiB2,823,711,2645.616bartowski
Q5_K_S2.63 GiB2,823,711,4245.616mradermacher
Q5_K_M2.69 GiB2,889,513,5045.747bartowski
Q5_K_M2.69 GiB2,889,513,6645.747mradermacher
Q5_K_L2.78 GiB2,983,713,8245.934bartowski
Q6_K3.08 GiB3,306,261,0246.576bartowski
Q6_K3.08 GiB3,306,261,1846.576mradermacher
Q6_K_L3.17 GiB3,400,461,3446.763bartowski
Q8_03.99 GiB4,280,405,0248.513bartowski
Q8_03.99 GiB4,280,405,1848.513mradermacher
BF167.50 GiB8,051,284,73616.013bartowski
F167.50 GiB8,051,285,18416.013mradermacher

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.56 GiB0.56 GiB36 / 0 / 0
8,1921.13 GiB1.13 GiB36 / 0 / 0
16,3842.25 GiB2.25 GiB36 / 0 / 0
32,7684.50 GiB4.50 GiB36 / 0 / 0
65,5369.00 GiB9.00 GiB36 / 0 / 0
131,07218.00 GiB18.00 GiB36 / 0 / 0

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 2.11 GiB. The real file is 2.33 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
36
Attention heads
32
KV heads
8
Head dim
128
Hidden size
2560
Vocab
151,936
Sliding window
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window
false

Questions people ask

How much VRAM does Qwen3-4B-abliterated need?
Q4_K_M is exactly 2,497,280,544 bytes (2.33 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen3-4B-abliterated's KV cache?
4.50 GiB at 32K context with an f16 cache, computed per layer. Quantizing the cache to q8_0 roughly halves it, which is often the difference between a context length fitting and not.
Which quantization of Qwen3-4B-abliterated 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.