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Fourier-Qwen2.5-VL-3B-0.67

whyisverysmart/Fourier-Qwen2.5-VL-3B-0.67

Fourier-Qwen2.5-VL-3B-0.67 at I1-IQ1_S is exactly 791,093,440 bytes (0.74 GiB / 0.79 GB) — an effective 1.686 bits per weight, not the nominal 1. Its KV cache at 32K is 1.13 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
3.8B
Architecture
qwen2vl
36 layers
Context
128,000
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S0.74 GiB791,093,4401.686mradermacher
I1-IQ1_M0.79 GiB850,026,6881.811mradermacher
I1-IQ2_XXS0.88 GiB948,248,7682.020mradermacher
I1-IQ2_XS0.96 GiB1,031,545,0242.198mradermacher
I1-IQ2_S0.99 GiB1,061,937,3442.263mradermacher
I1-IQ2_M1.06 GiB1,140,515,0082.430mradermacher
I1-Q2_K_S1.12 GiB1,198,127,2962.553mradermacher
I1-Q2_K1.19 GiB1,274,755,2642.716mradermacher
I1-IQ3_XXS1.19 GiB1,282,826,4322.733mradermacher
I1-IQ3_XS1.30 GiB1,391,835,3282.966mradermacher
I1-Q3_K_S1.35 GiB1,454,356,6723.099mradermacher
I1-IQ3_S1.36 GiB1,456,863,4243.104mradermacher
I1-IQ3_M1.39 GiB1,488,894,1443.172mradermacher
I1-Q3_K_M1.48 GiB1,590,474,9443.389mradermacher
I1-Q3_K_L1.59 GiB1,707,391,1683.638mradermacher
I1-IQ4_XS1.62 GiB1,739,094,2083.705mradermacher
I1-IQ4_NL1.70 GiB1,825,208,5123.889mradermacher
I1-Q4_01.70 GiB1,828,485,3123.896mradermacher
I1-Q4_K_S1.71 GiB1,834,383,5523.909mradermacher
I1-Q4_K_M1.80 GiB1,929,902,2724.112mradermacher
I1-Q4_11.86 GiB1,996,257,4724.253mradermacher
I1-Q5_K_S2.02 GiB2,169,665,7284.623mradermacher
I1-Q5_K_M2.07 GiB2,224,814,2724.740mradermacher
I1-Q6_K2.36 GiB2,538,158,2725.408mradermacher

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.14 GiB0.14 GiB36 / 0 / 0
8,1920.28 GiB0.28 GiB36 / 0 / 0
16,3840.56 GiB0.56 GiB36 / 0 / 0
32,7681.13 GiB1.13 GiB36 / 0 / 0
65,5362.25 GiB2.25 GiB36 / 0 / 0
131,0724.50 GiB4.50 GiB36 / 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 1.97 GiB. The real file is 0.74 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
36
Attention heads
16
KV heads
2
Head dim
128
Hidden size
2048
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-Qwen2.5-VL-3B-0.67 need?
I1-IQ1_S is exactly 791,093,440 bytes (0.74 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-Qwen2.5-VL-3B-0.67's KV cache?
1.13 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-Qwen2.5-VL-3B-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.