Model comparison

rfdetr vs gpt2

These two publish different quantization sets; the table below has the exact sizes.

From the file· summed bytes, KV per layer

Side by side

rfdetrgpt2
Parameters30M137M
Architecturerfdetrgpt2
Layers12
Native context
Mixture of expertsnono
Quantizations published1249
Smallest quantization0.03 GiB0.06 GiB
Q4_K_M0.11 GiB
Licenceapache-2.0

KV cache by context

the term that decides long-context viability
Contextrfdetrgpt2Ratio
4,096
8,192
16,384
32,768
65,536
131,072