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gemma-3n-E4B-it-5bit

mlx-community/gemma-3n-E4B-it-5bit
Vision + text · transformers
5-bit Open on Hugging Face
Parameters
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Weights (est.)
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Mac memory (est.)
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Size is estimated from the parameter count and quantisation. Memory allows a fifth extra for context plus 2 GB for the system; long contexts need more.

Run it

With mlx-vlm on an Apple silicon Mac:

pip install mlx-vlmpython -m mlx_vlm.generate --model mlx-community/gemma-3n-E4B-it-5bit --image photo.jpg --prompt "Describe this image"

Details

Base model
google/gemma-3n-E4B (quantized)
Vendor
Google · Gemma
Task
Vision + text
Quantisation
5-bit
Licence
gemma
Downloads
55 in the last 30 days · 1.6K all time · 0 likes
Published
2025-06-28 · updated 2025-07-12 (1y ago)
Tags
gemma3n, automatic-speech-recognition, automatic-speech-translation, audio-text-to-text, video-text-to-text

Other MLX builds of google/gemma-3n-E4B

Build Quantisation Weights Mac memory Downloads
gemma-3n-E2B-3bit 3-bit ≈ 3.9 GB 8 GB+ 25
gemma-3n-E2B-4bit 4-bit ≈ 4.5 GB 8 GB+ 68
gemma-3n-E4B-it-3bit 3-bit ≈ 5.0 GB 8 GB+ 31
gemma-3n-E2B-5bit 5-bit ≈ 5.0 GB 8 GB+ 33
gemma-3n-E2B-bf16 bf16 ≈ 10.9 GB 16 GB+ 70
gemma-3n-E4B-it-bf16 bf16 ≈ 15.7 GB 24 GB+ 161
gemma-3n-E4B-it-4bit 4-bit — — 425
gemma-3n-E4B-it-5bit (this one) 5-bit — — 55
gemma-3n-E4B-it-8bit 8-bit — — 50
gemma-3n-E2B-8bit 8-bit — — 40
gemma-3n-E4B-it-6bit 6-bit — — 32
gemma-3n-E2B-6bit 6-bit — — 23