jkim96

Mistral-Medium-3.5-128B-DASHQ-INT2-g32

Dedicated Endpoints

Run this model inference on single tenant GPU with unmatched speed and reliability at scale.

Container

Run this model inference with full control and performance in your environment.

Get help setting up a custom Dedicated Endpoints.

Talk with our engineer to get a quote for reserved GPU instances with discounts.

License: other

bash
pip install git+https://github.com/JaeminK/dashq.git

python
from dashq import load_quantized

model, tokenizer = load_quantized("jkim96/Mistral-Medium-3.5-128B-DASHQ-INT2-g32", device_map="auto")

Full zero-shot / few-shot results for every DASH-Q checkpoint: github.com/JaeminK/dashq#benchmarks

Model provider

jkim96

Model tree

Base

mistralai/Mistral-Medium-3.5-128B

Quantized

this model

Modalities

Input

Text

Output

Text

Pricing

Dedicated Endpoints

Supported Functionality

Model APIs

Dedicated Endpoints

Container

More information