Recipe by Mia's AI Lab @MiaAI_lab · based on turboderp, Qwen, DeepSeek, z-lab, r0b0tlab
Original recipe · Site · GitHub · X
License: Kit scripts: MIT · turboderp: MIT (engine), Apache-2.0 (quants) · Qwen: Apache-2.0 · DeepSeek: MIT · z-lab: MIT.
TESTED BY Mia's AI Lab on one RTX 5090 (32 GB), Linux, driver 610.43.02, ExLlamaV3 1.6.0 (pinned) · their results (benchmark table)
Qwen3.8-27B one-click kit for NVIDIA cards
EASY on Windows: one double-click. Linux: 2 commands.
bash linux/setup.sh
bash linux/start.shHER TUNED SETTINGS FOR A 24 GB CARD
CONTEXT_SIZE=262144 # full 262K context
GPU_MEM_GB=22 # room for driver
CACHE_QUANT=4 # int4 KV, near-lossless
DRAFT=mtp # faster replies
HOST=127.0.0.1 # keeps API privateSetup writes these for you when you take the 24 GB default. Paste only to set them by hand. From README 1, README 2, README 3.
OR · LET A CODING AGENT DO IT
Set up the Qwen3.8-27B one-click kit by Mia's AI Lab on this computer: https://github.com/MiaAI-Lab/Qwen3.8-27B-16gb-NVIDIA-GPUs-one-click-install
Follow its README exactly.
1. Check first and tell me what you find: NVIDIA card with 16 to 32 GB of VRAM, driver 570+, 64-bit Python 3.11+, Node 22.19+. Stop if any is missing.
2. Do not install anything system-wide or as admin. The kit keeps everything in its own folder.
3. Run the kit's setup, then start it. Accept the size it recommends.
4. In .env, make sure these are set: CONTEXT_SIZE=262144, GPU_MEM_GB=22, CACHE_QUANT=4, DRAFT=mtp, HOST=127.0.0.1 (keep HOST=127.0.0.1 unless I say this network is mine).
5. Run the kit's doctor command and show me the result.
6. Give me the full chat address it prints, token included.
Ask me before deleting anything.If it fails
It loads but replies crawl (Windows).
Close what holds graphics memory (browser, games, Discord, other AI apps). The start script lists them. Or lower CONTEXT_SIZE in .env.
"Images: off" when it starts.
The image part did not fit. Lower CONTEXT_SIZE and restart, or pick a smaller size.
Linux: "Insufficient VRAM in split for model and cache".
Lower CONTEXT_SIZE or GPU_MEM_GB in .env, or run ./linux/simplex setup and pick a smaller size.
The chat says authentication required.
Open the full address printed in the window or in logs/, with the token.
Anything else.
Windows: windows\simplex.bat doctor. Linux: ./linux/simplex doctor
From the original README, shortened. Read it for full details.
What they tested
- Speed (RigMark 1.3.0, median of 5 runs) and quality (MMLU 200 questions, GSM8K 100) on the RTX 5090 · evidence
- How much context fits, measured under 14.7 GB and 22.1 GB memory caps, Sep 6, 2026. The README does not name the card for these runs. · evidence
- 16 GB baseline: memory use measured at load under a 14.7 GB cap · evidence
- Engine version pinned (ExLlamaV3 v1.6.0); start scripts refuse other versions; unit tests in tests/ · evidence
Not shown in their results: No published Windows test results. No published run on a 24 GB card; the 24 GB default comes from the 22.1 GB cap measurement. No CI.
RunCards does not test recipes. We only list recipes whose authors publish their own test results. Checked 2026-10-19.
Who made what
- turboderp: ExLlamaV3 engine and the EXL3 quants (2.5 bpw and up) (also)
- Qwen: the Qwen3.8-27B model
- DeepSeek: DeepSeek Harness, the chat app it opens
- z-lab: DFlash2 (optional speed-up, 32 GB cards only)
- r0b0tlab: EXL3 quant of the DFlash2 drafter (optional)
The kit's README names these in its intro, its Engine line and its Credits line.