Qwen · text · mixture of experts

Qwen3-30B-A3B

Qwen/Qwen3-30B-A3B

Qwen3-30B-A3B at Q4_K_M is exactly 18,556,685,824 bytes (17.28 GiB / 18.56 GB) — an effective 4.862 bits per weight, not the nominal 4. Its KV cache at 32K is 3.00 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
30.5B
total, not active
Architecture
qwen3moe
48 layers
Context
40,960
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_XXS7.59 GiB8,146,266,7842.135bartowski
UD-IQ1_S8.42 GiB9,043,300,9282.369unsloth
IQ2_XS8.51 GiB9,140,316,8322.395bartowski
IQ2_S8.59 GiB9,222,251,1682.416bartowski
UD-IQ1_M9.00 GiB9,666,859,5842.533unsloth
UD-IQ2_XXS9.65 GiB10,362,262,0802.715unsloth
IQ2_M9.71 GiB10,430,210,7202.733bartowski
UD-IQ2_M10.12 GiB10,865,578,5602.847unsloth
Q2_K10.16 GiB10,908,648,0962.858bartowski
Q2_K_L10.44 GiB11,212,520,0962.938bartowski
Q2_K10.49 GiB11,258,610,2402.950unsloth
Q2_K_L10.55 GiB11,331,539,5202.969unsloth
IQ3_XXS11.38 GiB12,216,984,2243.201bartowski
IQ3_XS11.86 GiB12,736,461,4723.337bartowski
UD-IQ3_XXS12.00 GiB12,888,085,0563.377unsloth
Q3_K_S12.38 GiB13,292,468,8003.483unsloth
Q3_K_S12.51 GiB13,428,128,4163.518bartowski
IQ3_M13.11 GiB14,076,541,6003.688bartowski
Q3_K_M13.11 GiB14,076,803,7443.688579bartowski
Q3_K_L13.58 GiB14,583,003,8083.821bartowski
Q3_K_M13.70 GiB14,711,847,4883.855579unsloth
IQ4_XS15.25 GiB16,378,073,6644.291579unsloth
IQ4_XS15.33 GiB16,458,003,1044.312579bartowski
IQ4_NL16.12 GiB17,310,782,0164.536unsloth
Q4_016.19 GiB17,379,988,0324.554579unsloth
IQ4_NL16.19 GiB17,386,279,5844.556bartowski
Q4_K_S16.26 GiB17,456,009,7924.574unsloth
Q4_016.42 GiB17,631,646,3684.620579bartowski
Q4_K_S16.75 GiB17,984,492,1924.712bartowski
Q4_K_M17.28 GiB18,556,685,8244.862579Qwen
Q4_K_M17.28 GiB18,556,686,9124.862unsloth
Q4_K_M17.35 GiB18,632,184,4804.882bartowski
Q4_K_L17.57 GiB18,863,127,2004.942bartowski
Q4_117.87 GiB19,192,500,8005.029unsloth
Q4_117.89 GiB19,214,520,9925.035bartowski
Q5_019.63 GiB21,080,509,9525.524Qwen
Q5_K_S19.63 GiB21,080,511,0405.524unsloth
Q5_K_S19.65 GiB21,099,385,5045.528bartowski
Q5_K_M20.23 GiB21,725,580,8005.692579Qwen
Q5_K_M20.23 GiB21,725,581,8885.692unsloth

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.38 GiB0.38 GiB48 / 0 / 0
8,1920.75 GiB0.75 GiB48 / 0 / 0
16,3841.50 GiB1.50 GiB48 / 0 / 0
32,7683.00 GiB3.00 GiB48 / 0 / 0
65,5366.00 GiB6.00 GiB48 / 0 / 0
131,07212.00 GiB12.00 GiB48 / 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 15.99 GiB. The real file is 17.28 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
48
Attention heads
32
KV heads
4
Head dim
128
Hidden size
2048
Vocab
151,936
Sliding window
none
SWA period
MLA
no
Experts
128
Experts per token
8
use_sliding_window
false

Questions people ask

How much VRAM does Qwen3-30B-A3B need?
Q4_K_M is exactly 18,556,685,824 bytes (17.28 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen3-30B-A3B's KV cache?
3.00 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.
Is Qwen3-30B-A3B a mixture-of-experts model?
Yes — 128 experts, 8 routed per token. Every expert must be resident, but only the routed ones are read per token, which is why its memory requirement and its speed behave very differently.
Which quantization of Qwen3-30B-A3B 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.