[D] 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)

[Mixtral Experiments](https://preview.redd.it/i7mbjzl74hfc1.png?width=1600&format=png&auto=webp&s=1bb27c889d3b76a50b33cd549a7156702b5b4ae3)

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

Keen to hear your experiences and learnings in similar deployments!

a100 inference key libraries machinelearning max mixtral multiple performance pytorch rate sec thoughts token tokens