Sanitfy check my Qwen3.8 5090 Results; new to Local AI

A user running Qwen3.8-27B on an NVIDIA RTX 5090 32 GB with LM Studio reports decode speeds ranging from 12.38 to 47.4 tok/s depending on quantization and multi-token prediction settings, with the Q4_K_M quant achieving the fastest speed at ~47.4 tok/s and ~22.9 GB VRAM usage. The user, who works in AI adoption, governance, and cybersecurity, is building a 20-40b MCP server for red/blue teaming with Kali and seeks feedback on whether their setup and results are optimal.

Hey Everyone First post, kinda shy, be gentle So - I don’t have a TON of experience in Local AI - I do work in the AI Adoption / Governance / Cybersecurity Space, and am lucky enough to have active subscriptions across every major frontier model - however, I haven’t messed with Local AI in about 8 months. But - I’ve been hearing a ton about Qwen3.8-27b, so I loaded it up on my rig at the house in LM Studio, and ran a few tests with a harness doing some pentesting on a dev vm, and was pretty happy with the initial results, though it did get stuck in a few loops which ate through my context. So - I’m now in the process of building a 20-40b focused MCP server specifically for red teaming / blue teaming with Kali. Before I get too deep in that process I’m around 15ish hours in so far - I want to get some opinions on if my initial testing is “Stupid” or “The old way”. This is my current setup: | HW | Spec | |---|---| | CPU | Intel Core i9-13900K | | GPU | NVIDIA RTX 5090 32 GB | | RAM | 64 GB 7200 MT/s DDR5 | | OS | Windows | I’m using LM Studio right now - which I’m sure isn’t great - but this is the only thing I’ve used for tasks like these - open to suggestions if this is the wrong setup. Below is the performance I have been getting - this is another area I want a sanity check on. Before that, a bit of context for my decisions - this test was scoped specifically for a phased, agentic red team assessment on a single device. Below are my results: | Model / GGUF | Quant | MTP Max | Decode | Prompt Eval | Approx. VRAM | Relative Speed | |---|---|---|---|---|---|---| chimingw/Qwen3.8-27B-Uncensored-OrcaRouter-GGUF | Q6 K | 2 | 12.38 tok/s | 1,016.55 tok/s | ~28 GB | 1.00× | JonathanColetti/Qwen3.8-27B-Uncensored-GGUF | Q6 K | 1 | ~22.3 tok/s | — | ~27.5–28.5 GB | 1.80× | JonathanColetti/Qwen3.8-27B-Uncensored-GGUF | Q6 K | 2 | 31.60 tok/s | ~1,844.91 tok/s | ~27.5–28.5 GB | 2.55× | JonathanColetti/Qwen3.8-27B-Uncensored-GGUF | Q5 K M | 2 | ~44.7 tok/s | ~2,045.19 tok/s | ~26.3–26.5 GB | 3.61× | JonathanColetti/Qwen3.8-27B-Uncensored-GGUF | Q4 K M | 2 | ~47.4 tok/s | ~2,267.78 tok/s | ~22.9 GB | 3.83× | So - open ended question; give me your feedback. Should I switch away from LM Studio? Are my speeds decent? Am I leaving some performance on the table?