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Okay this is a fast and good model and a real community lift to get as stupid simple of a playbook for you as I could that solves THE NUMBER ONE critical request for Qwen 3.8 Flash Next, How can I get this running for my agent! This first off has some pretty hard yet also very achievable goals for a LOT of the local ai community that has been following along for the past few years. Many of you already have this but here is the specs needed to pull this off as I am here.
Requirements
Backstory/Notes
So first off, this may not be a super long lived way to accomplish this. vLLM has yet to get all the bits merged and there are some of these bits that may not make it into main but this works today and I wanted this to work TODAY. I saw a post on X and I got very excited about it. https://x.com/loktar00/status/2093907946484678922 and after reading the repo a bit I was maybe a bit less excited because holy crap Claude BUT I did determine there was one of these paths I wanted to go down and max out my performance on this model. I have spent around 12 hours chatting with Qwen 3.8 Flash Next so far and it really is very smart for such a sparse model but I wanted more TPS and to be able to run my agent reliably off it. I did attempt off llama.cpp but it just ended up in timeouts and sucking when the ctx got to 45K. I knew the answer could be vLLM and this was my ticket! I only wanted to go down the moderate lane however and not pull in and have to calibrate the fp8 KV cache which does allow for the max speed and ctx window but I already am running this as an int4 which is form of quantization just like an NVFP4. Being a quality-maxxie I wanted to preserve something, and this also made the entire process much easier for me, and for you. Loktar rode the shoulders of https://x.com/superalesha and I am betting we all rode the shoulders of many LLMs (Claude and Qwen 3.8 27B for sure to get this.
Build Script
Hermes Setup
A few things you need to make sure you have set for your Hermes Agent which you likely already do, but just to be sure.
In your config.yaml
make sure you have the following set for ctx length and threshold just in case you have been running other configs like 0.65 which I like myself for qwen 3.8 27b
Video
Abductem! Prompt
References
https://huggingface.co/VnimanieAI/Qwen3.8-Flash-Next-W4A16
https://github.com/loktar00/qwen38-flash-next-vllm-3090-recipe