DavidAU · text

Gemma-The-Writer-9B-HERETIC-Uncensored-Abliterated

DavidAU/Gemma-The-Writer-9B-HERETIC-Uncensored-Abliterated

Gemma-The-Writer-9B-HERETIC-Uncensored-Abliterated at Q4_K_M is exactly 5,761,059,136 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 GiB2,378,566,2722.059mradermacher
I1-IQ1_M2.37 GiB2,545,953,4082.204mradermacher
I1-IQ2_XXS2.63 GiB2,824,931,9682.445mradermacher
I1-IQ2_XS2.86 GiB3,067,382,4002.655mradermacher
I1-IQ2_S2.99 GiB3,211,487,8722.780mradermacher
I1-IQ2_M3.20 GiB3,434,670,7202.973mradermacher
I1-Q2_K_S3.31 GiB3,552,512,6403.075mradermacher
I1-IQ3_XXS3.54 GiB3,796,740,7363.287mradermacher
Q2_K3.54 GiB3,805,399,3603.294mradermacher
I1-Q2_K3.54 GiB3,805,399,6803.294mradermacher
I1-IQ3_XS3.86 GiB4,144,990,8483.588mradermacher
Q3_K_S4.04 GiB4,337,666,3683.755mradermacher
I1-IQ3_S4.04 GiB4,337,666,6883.755mradermacher
I1-Q3_K_S4.04 GiB4,337,666,6883.755mradermacher
I1-IQ3_M4.19 GiB4,494,617,2163.891mradermacher
Q3_K_M4.43 GiB4,761,782,5924.122mradermacher
I1-Q3_K_M4.43 GiB4,761,782,9124.122mradermacher
Q3_K_L4.78 GiB5,132,454,2084.443mradermacher
I1-Q3_K_L4.78 GiB5,132,454,5284.443mradermacher
I1-IQ4_XS4.83 GiB5,183,031,9364.487mradermacher
IQ4_XS4.86 GiB5,223,172,4164.521mradermacher
I1-IQ4_NL5.07 GiB5,443,144,3204.712mradermacher
I1-Q4_05.08 GiB5,459,200,6404.726mradermacher
Q4_K_S5.10 GiB5,478,926,6564.743mradermacher
I1-Q4_K_S5.10 GiB5,478,926,9764.743mradermacher
Q4_K_M5.37 GiB5,761,059,1364.987mradermacher
I1-Q4_K_M5.37 GiB5,761,059,4564.987mradermacher
I1-Q4_15.55 GiB5,963,369,0885.162mradermacher
Q5_K_S6.04 GiB6,483,593,5365.612mradermacher
I1-Q5_K_S6.04 GiB6,483,593,8565.612mradermacher
Q5_K_M6.19 GiB6,647,368,0005.754mradermacher
I1-Q5_K_M6.19 GiB6,647,368,3205.754mradermacher
Q6_K7.07 GiB7,589,071,1686.569mradermacher
I1-Q6_K7.07 GiB7,589,071,4886.569mradermacher
Q8_09.15 GiB9,827,150,1448.507mradermacher
F1617.22 GiB18,490,681,66416.006mradermacher

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 Gemma-The-Writer-9B-HERETIC-Uncensored-Abliterated need?
Q4_K_M is exactly 5,761,059,136 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 Gemma-The-Writer-9B-HERETIC-Uncensored-Abliterated'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 Gemma-The-Writer-9B-HERETIC-Uncensored-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.