Experiments with Mixtral-8x7B using Multiple Libraries - Got max 52 tokens/sec. Thoughts?

Hi everyone,

Recently experimented with deploying the Mixtral-8x7B model and wanted to share key findings for those interested:

**Best Performance**: With Quantized 8-bit model using Pytorch(nightly) got an average token generation rate of 52.03 token/sec on A100, average inference of 4.94 seconds and cold-start 11.48 secs ( matters when deployed in serverless environment)

https://preview.redd.it/93l5oydhjvfc1.png?width=1600&format=png&auto=webp&s=300e6d690d3de995db86fedf633bec25d149b935

**Other Libraries Tested:** vLLM, AutoGPTQ, HQQ

Here is the link to the tutorial - [https://tutorials.inferless.com/deploy-mixtral-8x7b-for-52-tokens-sec-on-a-single-gpu](https://tutorials.inferless.com/deploy-mixtral-8x7b-for-52-tokens-sec-on-a-single-gpu)

Keen to hear your experiences and learnings in similar deployments!

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