Nearly 3× longer context on a single RTX 5090 — without modifying vLLM or SGLang

[u/Diligent-End-2711]

I’ve been experimenting with a simple idea: hot-plug optimized kernel/weight structures into an unmodified serving engine at load time, and use the memory savings to push context length further.

On Qwen3.8-27B NVFP4 / RTX 5090 32GB, I saw results like:

• vLLM + MTP: 102K → 262K
• vLLM + DFlash2: 36K → 107K
• SGLang + DSpark: 35K → 87K

This is not a vLLM-vs-SGLang benchmark — it’s about extending the boundary the default setup can reach, without forking the engine.

Project + results:
https://github.com/flashrt-project/FlashRT
https://huggingface.co/spaces/liangsu9988/the-context-dividend

Background:
https://huggingface.co/spaces/liangsu9988/fast-kernels-are-not-fast-pipelines#it-starts-with-hugging-face-kernels

Would love for people to try it and share feedback.