OccultAI · text

G2-Darkest-Writer-Dirty-Shirley-9B-v2

OccultAI/G2-Darkest-Writer-Dirty-Shirley-9B-v2

G2-Darkest-Writer-Dirty-Shirley-9B-v2 at Q4_K_M is exactly 5,761,058,176 bytes (5.37 GiB / 5.76 GB) — an effective 4.987 bits per weight, not the nominal 4. Its KV cache at 32K is 5.99 GiB, not the 10.50 GiB a flat formula predicts.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
9.2B
Architecture
gemma2
42 layers
Context
8,192
native (config.json)
License

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S2.22 GiB2,378,565,3122.059mradermacher
I1-IQ1_M2.37 GiB2,545,952,4482.204mradermacher
I1-IQ2_XXS2.63 GiB2,824,931,0082.445mradermacher
I1-IQ2_XS2.86 GiB3,067,381,4402.655mradermacher
I1-IQ2_S2.99 GiB3,211,486,9122.780mradermacher
I1-IQ2_M3.20 GiB3,434,669,7602.973mradermacher
I1-Q2_K_S3.31 GiB3,552,511,6803.075mradermacher
I1-IQ3_XXS3.54 GiB3,796,739,7763.287mradermacher
Q2_K3.54 GiB3,805,398,4003.294mradermacher
I1-Q2_K3.54 GiB3,805,398,7203.294mradermacher
I1-IQ3_XS3.86 GiB4,144,989,8883.588mradermacher
Q3_K_S4.04 GiB4,337,665,4083.755mradermacher
I1-IQ3_S4.04 GiB4,337,665,7283.755mradermacher
I1-Q3_K_S4.04 GiB4,337,665,7283.755mradermacher
I1-IQ3_M4.19 GiB4,494,616,2563.891mradermacher
Q3_K_M4.43 GiB4,761,781,6324.122mradermacher
I1-Q3_K_M4.43 GiB4,761,781,9524.122mradermacher
Q3_K_L4.78 GiB5,132,453,2484.443mradermacher
I1-Q3_K_L4.78 GiB5,132,453,5684.443mradermacher
I1-IQ4_XS4.83 GiB5,183,030,9764.487mradermacher
IQ4_XS4.86 GiB5,223,171,4564.521mradermacher
I1-IQ4_NL5.07 GiB5,443,143,3604.712mradermacher
I1-Q4_05.08 GiB5,459,199,6804.726mradermacher
Q4_K_S5.10 GiB5,478,925,6964.743mradermacher
I1-Q4_K_S5.10 GiB5,478,926,0164.743mradermacher
Q4_K_M5.37 GiB5,761,058,1764.987mradermacher
I1-Q4_K_M5.37 GiB5,761,058,4964.987mradermacher
I1-Q4_15.55 GiB5,963,368,1285.162mradermacher
Q5_K_S6.04 GiB6,483,592,5765.612mradermacher
I1-Q5_K_S6.04 GiB6,483,592,8965.612mradermacher
Q5_K_M6.19 GiB6,647,367,0405.754mradermacher
I1-Q5_K_M6.19 GiB6,647,367,3605.754mradermacher
Q6_K7.07 GiB7,589,070,2086.569mradermacher
I1-Q6_K7.07 GiB7,589,070,5286.569mradermacher
Q8_09.15 GiB9,827,149,1848.507mradermacher
F1617.22 GiB18,490,680,70416.006mradermacher

KV cache by context

computed per layer — this model uses sliding-window attention
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0961.31 GiB1.31 GiB21 / 21 / 0
8,1922.05 GiB2.63 GiB1.28×21 / 21 / 0
16,3843.36 GiB5.25 GiB1.56×21 / 21 / 0
32,7685.99 GiB10.50 GiB1.75×21 / 21 / 0
65,53611.24 GiB21.00 GiB1.87×21 / 21 / 0
131,07221.74 GiB42.00 GiB1.93×21 / 21 / 0

21 of 42 layers cache only a 4,096-token window rather than the full context, on a period of 2. Figures assume the default configuration; --swa-full disables the saving entirely.

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 4.84 GiB. The real file is 5.37 GiB, because a quantization is a mixture and some tensors are always kept at higher precision. The larger discrepancy is the cache: a flat formula gives 10.50 GiB at 32K context where the real figure is 5.99 GiB, because most of this model's layers cache a fixed window rather than the whole context.

Architecture

from config.json
Layers
42
Attention heads
16
KV heads
8
Head dim
256
Hidden size
3584
Vocab
256,000
Sliding window
4096
SWA period
2
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does G2-Darkest-Writer-Dirty-Shirley-9B-v2 need?
Q4_K_M is exactly 5,761,058,176 bytes (5.37 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is G2-Darkest-Writer-Dirty-Shirley-9B-v2's KV cache?
5.99 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 G2-Darkest-Writer-Dirty-Shirley-9B-v2 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.