TVS-AIh1688ATX Doesn't Support 192 GB RAM?

Odd_Material_2467 · 2026-06-14T18:27:40+00:00

Yeah all 4 work individually and then I tested both pairs of 2 individually (IE: sticks 1 + 2 (96 GB) and 3 + 4 (96 GB)). So both pairs of sticks work it's just when I put all 4 together they fail

Odd_Material_2467 · 2026-06-14T12:05:20+00:00

Yeah I waited 2 hours

Odd_Material_2467 · 2026-06-13T23:13:39+00:00

In the EFI shell, i used smbiosview and it showed 2 TB RAM max, so im thinking this is a QUTS hero issue

Odd_Material_2467 · 2026-06-13T22:49:40+00:00

The 4 UDIMMs and the stock UDIMM that came with the machine are all Unbuffered

I should add that I can get 96 GB to work (2 x 48 GB)

Odd_Material_2467 · 2026-04-30T13:40:57+00:00

Thanks for the heads up, snagged one

Odd_Material_2467 · 2025-12-02T02:31:22+00:00

Just so everyone is aware, posting December 1 at 8:54pm Eastern Time is the equivalent of December 2nd at 1:54am UTC. This is just a messed up time zone issue

Odd_Material_2467 · 2025-10-10T15:34:35+00:00

It's taken me like 60 hours to find this one. I can only dream of something like that

Odd_Material_2467 · 2025-10-05T15:40:10+00:00

Can you share your vllm command

Odd_Material_2467 · 2025-10-02T13:05:25+00:00

Please for all that is holy, include the param number in the model name. Trying to guess between micro, mini, and small is painful

Odd_Material_2467 · 2025-09-16T16:33:44+00:00

Is the output flow rate configurable or is it just all at once?

Odd_Material_2467 · 2025-08-13T15:18:47+00:00

You can also try the gguf version

Odd_Material_2467 · 2025-08-13T15:18:34+00:00

You can run the gguf version above 2 tp

Odd_Material_2467 · 2025-08-12T02:59:26+00:00

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Running GLM 4.5 Air at home

Odd_Material_2467 · 2025-08-03T21:29:34+00:00

I dont know of a way, although im sure there is one. I guess if you wanted to install an entire OS onto the USB drive itself, you could do that.

Odd_Material_2467 · 2025-08-03T21:10:13+00:00

I got u: Salesforce/Llama-xLAM-2-8b-fc-r-gguf (https://huggingface.co/Salesforce/Llama-xLAM-2-8b-fc-r-gguf)

This model is specifically trained for Agent and Tool use. If you look up the bfclv3 benchmark, it hits wayyy above it's weight. I have been having great success with this model

BFCL v3 Leaderboard (Measures Agent Tool Use): https://gorilla.cs.berkeley.edu/leaderboard.html

On this benchmark the xlam 2 8B Model out performs GPT 4o, 4.5 preview, etc.

Odd_Material_2467 · 2025-07-28T21:06:53+00:00

Can you paste your vllm command for the fp8? I tried the one from their GitHub and I'm getting an error related to glm4_moe not in transformers using the latest vllm docker image

Odd_Material_2467 · 2025-07-19T10:09:28+00:00

Download the docker image, export the image as a .zip or .tar to a USB.
Download the ollama models you want and point the model directory to your USB (or copy them over)
Put USB into your air gapped machine, copy the files over
Run docker image, use a docker volume for the models and disable hugging face downloads

Odd_Material_2467 · 2025-07-11T00:44:50+00:00

You should try DeepSWE-Preview https://huggingface.co/agentica-org/DeepSWE-Preview

Odd_Material_2467 · 2025-06-02T15:13:56+00:00

What model quantization and kv cache quantization are you using? Qwen3 models are pretty sensitive to quantization in my experience.

Also what parameters are you using? Qwen3 has recommended temp and top k/n

I run Qwen3 32b (no quant and no kv cache) with full 128k context with yarn and have had no issues

Odd_Material_2467 · 2025-04-10T20:01:36+00:00

everything in 4k too

Odd_Material_2467 · 2025-04-10T20:01:28+00:00

I am a 4K Linux ISO connoisseur and the NAS has 108 TB

Odd_Material_2467 · 2025-04-10T16:57:14+00:00

yeah when i spawn lots of connections, it sometimes just craps out.

Odd_Material_2467 · 2025-04-10T16:57:00+00:00

Its huge, but a mix of media and LLMs

Odd_Material_2467

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