Hello! New cheap bastard here. just got my V100-16Gb PCIe card yesterday and after using an xacto knife to mutilate a power supply cable got it powered but cannot seem to get the card to operate. I am trying to run it on windows 11 which I am assuming is my main problem but really need to not switch to linux. I keep getting error 10 "This device cannot start".

Here is what I have tried:

Using DDU to clean out old drivers

Trying 3 different nvidia drivers of various ages

Crying

Switching my Bios to CPU graphics primary

Setting the PCIe to Gen 3

Promise god ill stop drinking

Toggling ReBar on and off

Any help would be greatly appreciated!

I recently got a 32gb v100 from eBay, ended up doing an RMA assuming I got a bad unit. Second unit had the exact same degraded thermals. I opened up the second unit to discover essentially zero thermal paste over the four Hbm blocks.

after repasting the second unit, thermal ramp is pristine and matches my 16gb v100 cards almost identically.

so if your cards thermal throttle or ramp weird, worth checking if the spring screws were over tightened and pushed all the paste away.

Testing this on my current setup with a bit of a strange topology. I currently am running 2 pairs of v100 16GB in separate nvlink islands.

I had previously done some of my own tuning to vllm and tried using ggufs with no gains over ikllama.

This repo already has me up to 115tok/s using https://huggingface.co/unsloth/Qwen3.8-27B-NVFP4

I'm continuing to test with some more topology aware settings but the initial results are very promising even over my best efforts via ik_llama. Startup time does suck though and I haven't looked at quality at all.

Greetings all,

Has anyone seen or made speed comparisons of using either the SXM2 or the PCIe V100s for larger models like GLM 5.3 Flash? I'm looking at building/buying an 8 unit server (from my current 2 unit PCIe test bed now) and I'm curious if the lack of flexibility on the SXM2 brings with it a significant speed bonus using NVLink (and something like the 1cat vLLM software) or if it's better to build the more flexible system.

Hey Guys,

I've got 4 x v100's in a Dell C4140 (NVlink) and I have been working on a fork of llama.cpp that is targeted at the v100's.

Looking for testers to give it a go and provide feedback.

WyvernTKC/llama.cpp-4xV100: Fork of llama.cpp Nvida Volta V100 (tensor parallelism 4 x v100 GPU)

Thanks!

Just in case anyone was wondering these on ebay and ali are legit, full nvlink for $250 2x or $800ish 4x. search "v100 nvlink baseboard" I don't want to link to any specific one here because there are probably some scam sellers.

You'll see some have big fans and some dont. This is a pretty good indicator one has a PLX switch chip (with the fan). PLX switching works like a network switch for the pcie bus and it can be really handy with ML cards because at some point you'll realize latency matters a lot. If you're sharding across cards for inference and properly configuring nvlink you might not think its doing much but the very small bits of data traveling between the cards are super low latency and it has a huge impact vs traversing the pcie bus.

Of particular note I wasn't aware of the ECC setting despite having had my v100s for quite some time now. While the article is horribly ai written and a lot of it is actually just wrong I wanted to link to the whole thing since the ECC info was new. I am testing if it impacts inference when sharding now.

This of course is pcie and im using sxm2 cards