FINAL-Bench · text

Darwin-4B-Chimera

FINAL-Bench/Darwin-4B-Chimera

Darwin-4B-Chimera at Q4_K_M is exactly 2,497,281,088 bytes (2.33 GiB / 2.50 GB) — an effective 4.967 bits per weight, not the nominal 4. Its KV cache at 32K is 1.28 GiB, not the 4.50 GiB a flat formula predicts.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
4.0B
Architecture
qwen3
36 layers
Context
40,960
native (config.json)
License
gemma

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S0.98 GiB1,055,256,3842.099mradermacher
I1-IQ1_M1.05 GiB1,127,018,3042.241mradermacher
I1-IQ2_XXS1.16 GiB1,246,621,5042.479mradermacher
I1-IQ2_XS1.26 GiB1,354,100,5442.693mradermacher
I1-IQ2_S1.32 GiB1,417,301,8242.819mradermacher
I1-IQ2_M1.41 GiB1,512,984,3843.009mradermacher
I1-Q2_K_S1.46 GiB1,563,454,7843.109mradermacher
Q2_K1.55 GiB1,669,499,9683.320mradermacher
I1-Q2_K1.55 GiB1,669,500,2243.320mradermacher
I1-IQ3_XXS1.56 GiB1,670,188,8643.322mradermacher
IQ2_M1.58 GiB1,693,904,2883.369bartowski
Q2_K1.64 GiB1,762,397,0883.505bartowski
IQ3_XXS1.66 GiB1,782,255,0083.545bartowski
I1-IQ3_XS1.69 GiB1,814,375,7443.608mradermacher
Q2_K_L1.73 GiB1,856,597,4083.692bartowski
Q3_K_S1.76 GiB1,886,997,5683.753mradermacher
I1-Q3_K_S1.76 GiB1,886,997,8243.753mradermacher
I1-IQ3_S1.77 GiB1,899,531,5843.778mradermacher
IQ3_XS1.78 GiB1,910,221,7283.799bartowski
Q3_K_S1.83 GiB1,960,725,4083.900bartowski
I1-IQ3_M1.83 GiB1,962,896,7043.904mradermacher
IQ3_M1.91 GiB2,048,420,7684.074bartowski
Q3_K_M1.93 GiB2,075,618,3684.128mradermacher
I1-Q3_K_M1.93 GiB2,075,618,6244.128mradermacher
Q3_K_M2.01 GiB2,154,589,0884.285bartowski
Q3_K_L2.09 GiB2,239,786,0484.455mradermacher
I1-Q3_K_L2.09 GiB2,239,786,3044.455mradermacher
Q3_K_L2.11 GiB2,266,327,9684.507bartowski
I1-IQ4_XS2.11 GiB2,270,752,0644.516mradermacher
IQ4_XS2.13 GiB2,286,316,6084.547mradermacher
IQ4_XS2.18 GiB2,337,844,1284.650bartowski
I1-Q4_02.21 GiB2,375,773,5044.725mradermacher
I1-IQ4_NL2.22 GiB2,381,344,0644.736mradermacher
Q4_K_S2.22 GiB2,383,309,8884.740mradermacher
I1-Q4_K_S2.22 GiB2,383,310,1444.740mradermacher
Q4_02.26 GiB2,424,433,5684.822bartowski
Q4_K_S2.27 GiB2,436,557,7284.846bartowski
IQ4_NL2.27 GiB2,442,537,8884.858bartowski
Q4_K_M2.33 GiB2,497,281,0884.967mradermacher
I1-Q4_K_M2.33 GiB2,497,281,3444.967mradermacher

KV cache by context

computed per layer — this model uses sliding-window attention
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.56 GiB0.56 GiB6 / 30 / 0
8,1920.71 GiB1.13 GiB1.57×6 / 30 / 0
16,3840.90 GiB2.25 GiB2.49×6 / 30 / 0
32,7681.28 GiB4.50 GiB3.52×6 / 30 / 0
65,5362.03 GiB9.00 GiB4.44×6 / 30 / 0
131,0723.53 GiB18.00 GiB5.10×6 / 30 / 0

30 of 36 layers cache only a 4,096-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 2.11 GiB. The real file is 2.33 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 4.50 GiB at 32K context where the real figure is 1.28 GiB, because most of this model's layers cache a fixed window rather than the whole context.

Architecture

from config.json
Layers
36
Attention heads
32
KV heads
8
Head dim
128
Hidden size
2560
Vocab
151,936
Sliding window
4096
SWA period
MLA
no
Experts
Experts per token
use_sliding_window
true

Questions people ask

How much VRAM does Darwin-4B-Chimera need?
Q4_K_M is exactly 2,497,281,088 bytes (2.33 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Darwin-4B-Chimera's KV cache?
1.28 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 Darwin-4B-Chimera 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.