Model comparison

nomic-embed-text-v2-moe vs KaLM-embedding-multilingual-mini-instruct-v2.5

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

From the file· summed bytes, KV per layer

Side by side

nomic-embed-text-v2-moeKaLM-embedding-multilingual-mini-instruct-v2.5
Parameters475M494M
Architecturenomic-bert-moeqwen2
Layers1224
Native context131,072
Mixture of expertsyes, 8 expertsno
Quantizations published201
Smallest quantization0.25 GiB0.49 GiB
Q4_K_M0.32 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
Contextnomic-embed-text-v2-moeKaLM-embedding-multilingual-mini-instruct-v2.5Ratio
4,0960.05 GiB
8,1920.09 GiB
16,3840.19 GiB
32,7680.38 GiB
65,5360.75 GiB
131,0721.50 GiB