DavidAU · text · mixture of experts

Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored

DavidAU/Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored

Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored at Q4_K_M is exactly 20,414,848,064 bytes (19.01 GiB / 20.41 GB) — an effective 4.859 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
33.6B
total, not active
Architecture
qwen3moe
36 layers
Context
262,144
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S6.50 GiB6,983,652,9921.662mradermacher
I1-IQ1_M7.19 GiB7,723,144,8321.838mradermacher
I1-IQ2_XXS8.34 GiB8,955,631,2322.132mradermacher
I1-IQ2_XS9.27 GiB9,953,416,8322.369mradermacher
I1-IQ2_S9.43 GiB10,127,906,4322.411mradermacher
I1-IQ2_M10.35 GiB11,113,895,5522.645mradermacher
I1-Q2_K_S10.74 GiB11,532,473,4722.745mradermacher
I1-Q2_K11.53 GiB12,383,294,5922.948mradermacher
I1-IQ3_XXS12.11 GiB13,000,349,3123.095mradermacher
I1-IQ3_XS12.89 GiB13,837,948,0323.294mradermacher
I1-Q3_K_S13.60 GiB14,603,981,9523.476mradermacher
I1-IQ3_S13.61 GiB14,616,515,7123.479mradermacher
I1-IQ3_M13.81 GiB14,825,411,7123.529mradermacher
Q3_K_M15.06 GiB16,170,859,5843.849advanubis
Q3_K_M15.06 GiB16,170,859,5843.849DavidAU
I1-Q3_K_M15.06 GiB16,170,865,7923.849mradermacher
I1-Q3_K_L16.30 GiB17,499,280,5124.165mradermacher
I1-IQ4_XS16.76 GiB17,992,520,8324.283mradermacher
IQ4_XS16.93 GiB18,179,292,2244.327DavidAU
IQ4_XS16.93 GiB18,179,292,2244.327advanubis
I1-Q4_017.78 GiB19,090,576,5124.544mradermacher
Q4_K_S17.85 GiB19,166,592,0644.562DavidAU
Q4_K_S17.85 GiB19,166,592,0644.562advanubis
I1-Q4_K_S17.85 GiB19,166,598,2724.562mradermacher
Q4_K_M19.01 GiB20,414,848,0644.859DavidAU
Q4_K_M19.01 GiB20,414,848,0644.859advanubis
I1-Q4_K_M19.01 GiB20,414,854,2724.859mradermacher
I1-Q4_119.64 GiB21,092,045,9525.021mradermacher
Q5_K_S21.58 GiB23,168,220,2245.515advanubis
Q5_K_S21.58 GiB23,168,220,2245.515DavidAU
I1-Q5_K_S21.58 GiB23,168,226,4325.515mradermacher
Q5_K_M22.25 GiB23,888,911,4245.686advanubis
Q5_K_M22.25 GiB23,888,911,4245.686DavidAU
I1-Q5_K_M22.25 GiB23,888,917,6325.686mradermacher
Q6_K25.69 GiB27,580,103,7446.565DavidAU
Q6_K25.69 GiB27,580,103,7446.565advanubis
I1-Q6_K25.69 GiB27,580,109,9526.565mradermacher
Q8_033.27 GiB35,719,503,4248.502DavidAU
Q8_033.27 GiB35,719,503,4248.502advanubis

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 17.61 GiB. The real file is 19.01 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
12
Experts per token
2
use_sliding_window
false

Questions people ask

How much VRAM does Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored need?
Q4_K_M is exactly 20,414,848,064 bytes (19.01 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored'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.
Is Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored a mixture-of-experts model?
Yes — 12 experts, 2 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 Qwen3-48B-A4B-Savant-Commander-Distill-12X-Closed-Open-Heretic-Uncensored 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.