empero-ai · First MLX build 3 Aug 2026
Qwythos-27B-v1
MLX
TextVision apache-2.0
A 27B parameter vision and text model from empero-ai, with one MLX build at 4-bit.
- Parameters
- 27B From Hugging Face
- Quantisation
- 4-bit Qwythos-27B-v1-OptiQ-4bit
- Memory needed
- 20 GB Estimate, unified memory
- Download
- 16.1 GB Weights, estimated
- Downloads
- 304 This build, last 30 days
- Task
- Vision and text Text, Vision
- MLX builds
- 1 On mlx-community
- Devices
- Mac Apple silicon
Memory
Will it fit?Needs about 20 GB at 4-bit
8 GB
16 GB
24 GB
32 GB
64 GB
128 GB
Fits with headroomTight, close other appsWon’t fit
Estimated from the size of the weights, plus a fifth for context and working memory and 2 GB for macOS and your apps. Long contexts need more.
Run it
Terminal · mlx-vlm$ pip install -U mlx-vlm
$ python -m mlx_vlm.generate --model mlx-community/Qwythos-27B-v1-OptiQ-4bit --image photo.jpg --prompt "Describe this image"MLX builds
1 on mlx-community| Qwythos-27B-v1-OptiQ-4bit | 4-bit | 16.1 GB | 20 GB | 304 |
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Sizes are estimated from Hugging Face’s parameter counts and the quantisation. Downloads are for the last 30 days.