embeddinggemma-2-oQ3

This model was quantized using oQ (oMLX v0.7.1) mixed-precision quantization.

The effective average is 11.625 bits/weight for the complete checkpoint.

Quantization and Bit Distribution

Storage format Logical weights Share of total Tensor storage Effective bits/weight
Affine 3-bit, group 64 0.219B 29.441% 0.089 GiB 3.50
Affine 5-bit, group 64 0.037B 5.001% 0.024 GiB 5.50
Affine 6-bit, group 64 0.004B 0.563% 0.003 GiB 6.50
Affine 8-bit, group 64 0.012B 1.550% 0.011 GiB 8.50
BF16 0.472B 63.445% 0.880 GiB 16.00
Total 0.744B 100% 1.007 GiB 11.625

Storage Breakdown

Component Logical weights Storage
Language model 0.272B 0.137 GB / 0.128 GiB
Vision 0.167B 0.335 GB / 0.312 GiB
Audio 0.305B 0.610 GB / 0.568 GiB
Total 0.744B 1.082 GB / 1.007 GiB
Downloads last month
27
Safetensors
Model size
0.7B params
Tensor type
BF16
ยท
U32
ยท
MLX
Hardware compatibility
Log In to add your hardware

3-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Collection including bambocher/embeddinggemma-2-oQ3