I've tested myself and the results are legit, this is incredible, even if a little dangerous (it relies on a stack overwrite vulnerability in the signed Nvidia firmware).
> - you will need to run your card hotter than you might be comfortable with
Can you explain this one? On my GPU I didn't have to change the power limit. Obviously the card might spend more time at max power usage, but it's still within the limit.
It's quite nuanced. In a nutshell the unlock just flips the 2 bits that halves how often the core can issue the specific instructions Nvidia locks to full rate on the professional and datacenter cards.
Obviously doing more compute requires more power but what it does is shift the card down on the frequency curve to keep the wattage in check.
So you're right that at stock power limits it hits a cap where the full issuing rate isn't reached but it depends heavily on the exact workload how much juice is left.
The frequency curve also takes heat into account so in general you end up with a nice perf boost for a slightly hotter card at the same temperature.
I've been running this on my 2 3090s for a month now with no issues but they are also water cooled :-)
Ah, that's a twist I didn't see coming, all my GPUs are aircooled. I can see how with watercooling you'd be able to get more performance out of the GPU before hitting the limits.
There 3090 is from the era of overclocking, anything but the reference design should be fine even on air cooling (especially if you have a 3 connector model)
My EVGA came with stock firmware that started at a 420W and allowed up 500W, of course 500W did nothing for gaming
Uh, no. This headline is wrong. It's FP32 unlocked from being halved, not 16 bit ops. And to be clear, over the last week I've looked many places and I've not seen any reports of this unlock being applied to any 3xxx card except the 3090/3090ti series. Even if it might apply more generally in theory.
And also it does work on most 3000 series cards as they all run the same GA102 booter that's vulnerable :-)
There are some reports of cards with weird vbios layouts having issues but i'll try to get that fixed
Hey this is my work, although the exploits etc aren't my ideas by any means.
This is just a way to wrap the whole thing up in a much less annoying package than having to patch the nvidia driver. I originally got inspired by the CMP90/50 windows unlocks that run as standalone UEFI modules that chainloads into the OS.
I have a 3090 founders edition sitting on a shelf. The FE cards had VRM cooling issues, IIRC. Would this unlock have any uplift even if I undervolt and don't increase the power draw limits much? The use-case I'm thinking is to run a model to power a local only voice assistant for my family. I'm not really familiar with what instructions are used most heavily by LLMs, but is my read correct that this would be expected to help with TTFT? I'm curious if there's anything about this that helps in particular with audio processing models.
And maybe I'm overthinking the cooling issue. It's not like I'm hammering it 24/7. Probably fine to burst high on power draw on use.
Btw, I always love moments like this where library or project owners stumble on their work and chime in on the comments. I really appreciate your work here. It's given me motivation to actually do something with parts that have been sitting on a shelf.
You can trivially fix most of the VRM cooling issues btw by pulling the heat sink off, cleaning thoroughly and re applying fresh thermal pads. At this point almost all of 3090s are degraded in some way since those pads have a lifespan. The good news is it has nothing to do with the GPU itself.
I know it's probably not that difficult, but I always feel anxious doing things like that with expensive components. The thought of being slightly misaligned and causing issues gives me pause. I guess now that it's out of warranty, I have a bit less to lose.
really cool! would love to talk more if possible, sent a donation through ur github but if u can send me a dm on @chrs3775 on discord that would be appreciated
These firmwares are already fully encrypted but nvidia has been publishing encrypted debug images that turns out could be decrypted with one of their public test keys. And those debug firmwares turned out to be close enough to the production ones that they could be used to construct exploits from.
In this case it's a DMA buffer overflow that writes to the stack which in turn can be exploited with Return Oriented Programming. So no unsigned code is ever executed but we still have code execution control.
Honestly if Nvidia is going to be short on cards for years there is no reason to keep this locked. People are going to buy what they can get and this in no way is going to influence sales at this point by making it official.
The real gains are far less than the advertised.
Tests ton TFTOPS show 25% gains at 200Watt cap. While mostly prefil benefit from that less decoding which make the real gains 7-8%.
Using at full power:
This is a benchmark test with Qwen 27B Int4 with 4x3090 and using full batching on VLLM to squeeze every bit of the GPU's.
It worked for me, and I'm getting about 6% faster training on nanochat with my 3060 card. Thanks for this!
However, it required a few extra steps, as the repo is set up for Linux kernel 6.x and I'm on 5.15. Claude Code was able to get me past the hurdles, including code modifications and startup scripts.
Right now, I'm clearly power limited at 170 watts and I have no desire to brick my card or set it on fire.
As a person who uses consumer level hardware to do neural network research, this unlock is truly INVALUABLE.
This unlock is super useful as it improves the GPU performance on computation-bounded neural network workloads like LLM prefilling, image/video generation, and general neural network training, in a way of disabling deliberate software segmentation on the same hardware imposed by Nvidia.
I'm on rtx 50 series, and no free performance uplifting for now. Waiting for more reverse engineering efforts to reveal whether the unlock is possible for 50 series.
I'm aware that long-lasting reverse engineering efforts on nvidia gpus, like cmp gpus, will lead to something impactful. I just didn't see it clearly until your project came out. Good job on that.
For now, I think reverse engineering efforts on 50 series gpus are just beginning. There are projects like reading sensor temperatures directly from the gpu itself instead of using deliberately DOWNGRADED software like nvidia-smi. However, I don't really see these efforts spreading, and people behind them really needs more recognition. Props to all of you, too.
Certain (mostly AI) workloads. Depends on how hot you're comfortable running your card. The real-world improvement is considerably less due to other things being bottlenecks.
Can we unlock FP64 so we can do serious work on second order methods? Even at enterprise grade the last good fp64 gpu was the H100. B100 focused on lower fp due to llms.
I don't believe so. As I understand it, the only Ampere GPU with a full complement of FP64-capable cores is the GA100 used in the A-series server cards (which, as you suggest, still underperforms the H-series for FP64).
So yeah, buy an Nvidia card then download and run all the software needed to make it work to its full potential so Jensen can buy his 500 millionth leather jacket.
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[ 0.24 ms ] story [ 42.2 ms ] threadRepo for RTX 4090 and 4070 Ti Super: https://github.com/JustAResearcher/gpu-unlock-ada
https://github.com/KohakuBlueleaf/KohakUnlock
- you will need to run your card hotter than you might be comfortable with
- the real pay-off requires increasing the maximum power to 450W
- This is well above what the stock cooler was designed for so a bit more cooling would help
What's nice is that you can stack this mod on top of the p2p mod that has been out for a while, they don't seem to interfere with each other.
Can you explain this one? On my GPU I didn't have to change the power limit. Obviously the card might spend more time at max power usage, but it's still within the limit.
https://github.com/JustAResearcher/gpu-unlock-ada/releases/t...
Obviously doing more compute requires more power but what it does is shift the card down on the frequency curve to keep the wattage in check. So you're right that at stock power limits it hits a cap where the full issuing rate isn't reached but it depends heavily on the exact workload how much juice is left.
The frequency curve also takes heat into account so in general you end up with a nice perf boost for a slightly hotter card at the same temperature.
I've been running this on my 2 3090s for a month now with no issues but they are also water cooled :-)
My EVGA came with stock firmware that started at a 420W and allowed up 500W, of course 500W did nothing for gaming
On the other hand, this only applies to a limited set of workloads (training is often memory bandwidth bound for example).
I also wonder how this affects power consumption.
If its memory bandwidth bound you need to raise your batch sizes to leverage more parallelism.
And also it does work on most 3000 series cards as they all run the same GA102 booter that's vulnerable :-) There are some reports of cards with weird vbios layouts having issues but i'll try to get that fixed
Happy to answer questions!
https://pastebin.com/FAdBbGUd Qwen3.8-27B on an RTX 3090: Inference Options and Benchmark Results
And maybe I'm overthinking the cooling issue. It's not like I'm hammering it 24/7. Probably fine to burst high on power draw on use.
Btw, I always love moments like this where library or project owners stumble on their work and chime in on the comments. I really appreciate your work here. It's given me motivation to actually do something with parts that have been sitting on a shelf.
https://github.com/aikitoria/open-gpu-kernel-modules
The hardware supports it, but then Nvidia disabled it if the driver detects cheaper cards. This bypasses the NVidia slowdown.
In this case it's a DMA buffer overflow that writes to the stack which in turn can be exploited with Return Oriented Programming. So no unsigned code is ever executed but we still have code execution control.
This is a benchmark test with Qwen 27B Int4 with 4x3090 and using full batching on VLLM to squeeze every bit of the GPU's.
However, it required a few extra steps, as the repo is set up for Linux kernel 6.x and I'm on 5.15. Claude Code was able to get me past the hurdles, including code modifications and startup scripts.
Right now, I'm clearly power limited at 170 watts and I have no desire to brick my card or set it on fire.
This unlock is super useful as it improves the GPU performance on computation-bounded neural network workloads like LLM prefilling, image/video generation, and general neural network training, in a way of disabling deliberate software segmentation on the same hardware imposed by Nvidia.
I'm on rtx 50 series, and no free performance uplifting for now. Waiting for more reverse engineering efforts to reveal whether the unlock is possible for 50 series.
For now, I think reverse engineering efforts on 50 series gpus are just beginning. There are projects like reading sensor temperatures directly from the gpu itself instead of using deliberately DOWNGRADED software like nvidia-smi. However, I don't really see these efforts spreading, and people behind them really needs more recognition. Props to all of you, too.
Certain (mostly AI) workloads. Depends on how hot you're comfortable running your card. The real-world improvement is considerably less due to other things being bottlenecks.
https://github.com/keylase/nvidia-patch
So yeah, buy an Nvidia card then download and run all the software needed to make it work to its full potential so Jensen can buy his 500 millionth leather jacket.
[1] https://flopper.io/gpu/nvidia-geforce-rtx-3090-24gb [2] https://flopper.io/gpu/nvidia-geforce-rtx-3090-ti-24gb
This is why "right a reprogram" should exist. Anyone should be able to reverse-engineer and reprogram anything that has a CPU.
That's just modern corporate capitalism.
Manufacturing economics favour making everything the same for scale, while sale economics favour market segmentation.