llmfan46 · text

gemma-4-E2B-it-ultra-uncensored-heretic

llmfan46/gemma-4-E2B-it-ultra-uncensored-heretic

gemma-4-E2B-it-ultra-uncensored-heretic at Q4_K_M is exactly 3,094,874,720 bytes (2.88 GiB / 3.09 GB) — an effective 4.833 bits per weight, not the nominal 4. Its KV cache at 32K is 0.25 GiB, not the 1.09 GiB a flat formula predicts.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
5.1B
Architecture
gemma4
35 layers
Context
131,072
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M2.12 GiB2,280,213,0883.561JMingo
IQ3_XXS2.20 GiB2,362,346,0803.689JMingo
Q3_K_S2.27 GiB2,437,511,7763.806JMingo
Q3_K_M2.35 GiB2,527,392,3523.947JMingo
IQ4_XS2.77 GiB2,972,117,6004.641JMingo
I1-Q2_K2.78 GiB2,989,086,8484.668mradermacher
IQ4_NL2.82 GiB3,029,256,8004.730JMingo
Q4_02.82 GiB3,030,731,3604.733JMingo
Q4_K_S2.82 GiB3,033,287,2644.737JMingo
Q4_K_M2.88 GiB3,094,874,7204.833JMingo
I1-Q3_K_S2.90 GiB3,110,215,8084.857mradermacher
I1-IQ3_S2.90 GiB3,112,409,2164.860mradermacher
I1-IQ3_M2.92 GiB3,134,969,9844.895mradermacher
Q4_12.93 GiB3,143,092,8324.908JMingo
I1-Q3_K_M2.98 GiB3,201,349,7604.999mradermacher
I1-Q3_K_L3.06 GiB3,282,352,2565.125mradermacher
I1-IQ4_XS3.08 GiB3,303,929,9845.159mradermacher
Q5_K_S3.08 GiB3,308,145,2485.166JMingo
Q5_K_M3.11 GiB3,342,404,1925.219JMingo
I1-IQ4_NL3.13 GiB3,362,224,2565.250mradermacher
I1-Q4_03.13 GiB3,362,519,1685.251mradermacher
I1-Q4_K_S3.13 GiB3,365,075,0725.255mradermacher
I1-Q4_K_M3.19 GiB3,427,879,0405.353mradermacher
Q4_K_M3.19 GiB3,427,879,1365.353llmfan46
I1-Q4_13.24 GiB3,477,780,6085.431mradermacher
I1-Q5_K_S3.35 GiB3,595,401,3445.614mradermacher
Q5_K_S3.35 GiB3,595,401,4405.614llmfan46
I1-Q5_K_M3.38 GiB3,630,286,9765.669mradermacher
Q5_K_M3.38 GiB3,630,287,0725.669llmfan46
I1-Q6_K3.58 GiB3,845,345,4086.005mradermacher
Q6_K3.58 GiB3,845,345,5046.005llmfan46
Q6_K4.18 GiB4,486,208,0967.005JMingo
Q8_04.63 GiB4,967,495,9047.757llmfan46
Q8_04.68 GiB5,028,268,6407.852JMingo
BF168.64 GiB9,273,526,65614.481JMingo
BF168.67 GiB9,311,303,90414.540llmfan46

KV cache by context

computed per layer — this model uses sliding-window attention
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.05 GiB0.14 GiB2.50×7 / 28 / 0
8,1920.08 GiB0.27 GiB3.33×7 / 28 / 0
16,3840.14 GiB0.55 GiB4.00×7 / 28 / 0
32,7680.25 GiB1.09 GiB4.44×7 / 28 / 0
65,5360.46 GiB2.19 GiB4.71×7 / 28 / 0
131,0720.90 GiB4.38 GiB4.85×7 / 28 / 0

28 of 35 layers cache only a 512-token window rather than the full context, on a period of . 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 2.68 GiB. The real file is 2.88 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 1.09 GiB at 32K context where the real figure is 0.25 GiB, because most of this model's layers cache a fixed window rather than the whole context.

Architecture

from config.json
Layers
35
Attention heads
8
KV heads
1
Head dim
256
Hidden size
1536
Vocab
262,144
Sliding window
512
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does gemma-4-E2B-it-ultra-uncensored-heretic need?
Q4_K_M is exactly 3,094,874,720 bytes (2.88 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-4-E2B-it-ultra-uncensored-heretic's KV cache?
0.25 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-4-E2B-it-ultra-uncensored-heretic 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.