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Fourier-Qwen2-VL-2B-0.67

whyisverysmart/Fourier-Qwen2-VL-2B-0.67

Fourier-Qwen2-VL-2B-0.67 at I1-IQ1_S is exactly 436,526,912 bytes (0.41 GiB / 0.44 GB) — an effective 1.581 bits per weight, not the nominal 1. Its KV cache at 32K is 0.88 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
2.2B
Architecture
qwen2vl
28 layers
Context
32,768
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S0.41 GiB436,526,9121.581mradermacher
I1-IQ1_M0.43 GiB464,460,6081.682mradermacher
I1-IQ2_XXS0.48 GiB511,016,7681.851mradermacher
I1-IQ2_XS0.51 GiB550,326,0801.993mradermacher
I1-IQ2_S0.53 GiB563,809,0882.042mradermacher
I1-IQ2_M0.56 GiB601,054,0162.177mradermacher
I1-Q2_K_S0.60 GiB640,134,4642.318mradermacher
I1-IQ3_XXS0.62 GiB668,791,6162.422mradermacher
I1-Q2_K0.63 GiB676,304,1922.449mradermacher
I1-IQ3_XS0.68 GiB731,698,4962.650mradermacher
I1-Q3_K_S0.71 GiB760,943,9362.756mradermacher
I1-IQ3_S0.71 GiB762,406,2082.761mradermacher
I1-IQ3_M0.72 GiB776,663,3602.813mradermacher
I1-Q3_K_M0.77 GiB824,177,9842.985mradermacher
I1-Q3_K_L0.82 GiB880,162,1123.188mradermacher
I1-IQ4_XS0.83 GiB895,731,0083.244mradermacher
I1-IQ4_NL0.87 GiB936,330,5603.391mradermacher
I1-Q4_00.87 GiB937,534,7843.395mradermacher
I1-Q4_K_S0.88 GiB940,311,8723.405mradermacher
I1-Q4_K_M0.92 GiB986,047,8083.571mradermacher
I1-Q4_10.95 GiB1,016,841,5363.683mradermacher
I1-Q5_K_S1.02 GiB1,098,728,7683.979mradermacher
I1-Q5_K_M1.05 GiB1,125,049,6644.074mradermacher
I1-Q6_K1.19 GiB1,272,739,1364.609mradermacher

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.11 GiB0.11 GiB28 / 0 / 0
8,1920.22 GiB0.22 GiB28 / 0 / 0
16,3840.44 GiB0.44 GiB28 / 0 / 0
32,7680.88 GiB0.88 GiB28 / 0 / 0
65,5361.75 GiB1.75 GiB28 / 0 / 0
131,0723.50 GiB3.50 GiB28 / 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 I1-IQ1_S at roughly 1.16 GiB. The real file is 0.41 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
28
Attention heads
12
KV heads
2
Head dim
128
Hidden size
1536
Vocab
151,936
Sliding window
32768
SWA period
MLA
no
Experts
Experts per token
use_sliding_window
false

This model declares a sliding window but sets use_sliding_window: false, so the window is not applied. Honouring the field without the flag understates KV for the whole family.

Questions people ask

How much VRAM does Fourier-Qwen2-VL-2B-0.67 need?
I1-IQ1_S is exactly 436,526,912 bytes (0.41 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Fourier-Qwen2-VL-2B-0.67's KV cache?
0.88 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 Fourier-Qwen2-VL-2B-0.67 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.