arcflare_
Embedding300M official

embeddinggemma-300m

by Google

300M-parameter open embedding model from Google, built from Gemma 3 and trained on 100+ languages; 768-dim output with Matryoshka truncation.

#embedding#small
arcflare pull unsloth/embeddinggemma-300m-GGUF:Q8_0

[ 01 ] // quickstart

┌─ arcflare — zsh // tty1
$ 

[ 02 ] // readme

embeddinggemma-300m

300M-parameter open embedding model from Google, built from Gemma 3 and trained on 100+ languages; 768-dim output with Matryoshka truncation.

Get it

arcflare pull unsloth/embeddinggemma-300m-GGUF:Q8_0
arcflare run embeddinggemma-300m

ArcFlare reads the GGUF header and loads it at the largest context your free VRAM can actually hold. Use arcflare fit to see that before downloading anything else, or arcflare use opencode to code with it.

Highlights

  • Downloads the Q8_0 file by default: 0.33 GB. Also published: Q4_0 (0.28 GB), BF16 (0.61 GB), F32 (1.2 GB)
  • Trained for a 2K context
  • Licence: Gemma. Read it before commercial use

Sizes

  • 300m · 0.33GB

Other sizes live in sibling repos: swap the size in the repo name when pulling.

[ 03 ] // relatedmore →

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size
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vram
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license
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8% of a 24 GB card

#embedding #small

nomic-embed-text-v2-moe

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size
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vram
~2 GB
license
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8% of a 24 GB card

#embedding #small

bge-m3

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size
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vram
~2 GB
license
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8% of a 24 GB card

#embedding #small