How to use from
MLX LM
Generate or start a chat session
# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "deepsweet/GigaChat3.1-10B-A1.8B-MLX-oQ8"
Run an OpenAI-compatible server
# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "deepsweet/GigaChat3.1-10B-A1.8B-MLX-oQ8"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "deepsweet/GigaChat3.1-10B-A1.8B-MLX-oQ8",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'
Quick Links

This model was converted to MLX format from ai-sage/GigaChat3.1-10B-A1.8B using oMLX v0.2.24 with oQ Quantization.

Multi-Token Prediction (MTP) had to be disabled ("num_nextn_predict_layers": 0) and related layers had to be removed (model.layers.26.*).

Thanks RockTalk/GigaChat3.1-10B-A1.8B-MLX-4bit for the tip.

Settings:

  • Level: oQ8
  • Sensitivity model: none
  • Text Only: yes
Downloads last month
57
Safetensors
Model size
3B params
Tensor type
U8
·
U32
·
BF16
·
MLX
Hardware compatibility
Log In to add your hardware

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for deepsweet/GigaChat3.1-10B-A1.8B-MLX-oQ8

Quantized
(4)
this model

Collection including deepsweet/GigaChat3.1-10B-A1.8B-MLX-oQ8