shad0wcrawl3r · text

Qwen2.5-1.5B-heretic

shad0wcrawl3r/Qwen2.5-1.5B-heretic

Qwen2.5-1.5B-heretic at Q4_K_M is exactly 986,048,672 bytes (0.92 GiB / 0.99 GB) — an effective 5.110 bits per weight, not the nominal 4. Its KV cache at 32K is 0.88 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
1.5B
Architecture
qwen2
28 layers
Context
131,072
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S0.41 GiB436,528,0322.262mradermacher
I1-IQ1_M0.43 GiB464,461,7282.407mradermacher
I1-IQ2_XXS0.48 GiB511,017,8882.648mradermacher
I1-IQ2_XS0.51 GiB550,327,2002.852mradermacher
I1-IQ2_S0.53 GiB563,810,2082.922mradermacher
I1-IQ2_M0.56 GiB601,055,1363.115mradermacher
I1-Q2_K_S0.60 GiB640,135,5843.317mradermacher
I1-IQ3_XXS0.62 GiB668,792,7363.466mradermacher
Q2_K0.63 GiB676,305,0563.505mradermacher
I1-Q2_K0.63 GiB676,305,3123.505mradermacher
I1-IQ3_XS0.68 GiB731,699,6163.792mradermacher
Q3_K_S0.71 GiB760,944,8003.943mradermacher
I1-Q3_K_S0.71 GiB760,945,0563.943mradermacher
I1-IQ3_S0.71 GiB762,407,3283.951mradermacher
I1-IQ3_M0.72 GiB776,664,4804.025mradermacher
Q3_K_M0.77 GiB824,178,8484.271mradermacher
I1-Q3_K_M0.77 GiB824,179,1044.271mradermacher
Q3_K_L0.82 GiB880,162,9764.561mradermacher
I1-Q3_K_L0.82 GiB880,163,2324.561mradermacher
I1-IQ4_XS0.83 GiB895,732,1284.642mradermacher
IQ4_XS0.84 GiB902,183,0724.675mradermacher
I1-IQ4_NL0.87 GiB936,331,6804.852mradermacher
I1-Q4_00.87 GiB937,535,9044.859mradermacher
Q4_K_S0.88 GiB940,312,7364.873mradermacher
I1-Q4_K_S0.88 GiB940,312,9924.873mradermacher
Q4_K_M0.92 GiB986,048,6725.110mradermacher
I1-Q4_K_M0.92 GiB986,048,9285.110mradermacher
I1-Q4_10.95 GiB1,016,842,6565.270mradermacher
Q5_K_S1.02 GiB1,098,729,6325.694mradermacher
I1-Q5_K_S1.02 GiB1,098,729,8885.694mradermacher
Q5_K_M1.05 GiB1,125,050,5285.830mradermacher
I1-Q5_K_M1.05 GiB1,125,050,7845.830mradermacher
Q6_K1.19 GiB1,272,740,0006.596mradermacher
I1-Q6_K1.19 GiB1,272,740,2566.596mradermacher
Q8_01.53 GiB1,646,573,2168.533mradermacher
F162.88 GiB3,093,669,53616.032mradermacher

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 Q4_K_M at roughly 0.81 GiB. The real file is 0.92 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
none
SWA period
MLA
no
Experts
Experts per token
use_sliding_window
false

Questions people ask

How much VRAM does Qwen2.5-1.5B-heretic need?
Q4_K_M is exactly 986,048,672 bytes (0.92 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen2.5-1.5B-heretic'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 Qwen2.5-1.5B-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.