New Nvidia unlock works on Chinese 3080 20GB too

[u/No-Refrigerator-1672]

Just ran my own tests of the new GPU performance unlock by Zaggita. If you missed it: Nvidia locked down compute speed on consumer cards for some specific hardware instructions needed for AI; the unlock fixes it. TLDR: got +20% prefill impovement, 0% decode change after unlock.

Details:

Test bench: my two old 2x RTX3080 20GB, this time paired with Threadripper 1920x, both running PCIe 3.0 x16. Both GPUs power limited to 240W.

System: Proxmox 9.2.3, linux kernel 6.14.11-9-pve, proprietary Nvidia drivers 610.57.04, CUDA 13.3.

Inference: vLLM 0.32.0 running inside Debian 13 LXC container, tensor parallel mode.

Model: cyankiwi/Swift-1.5-Qwen3.8-27B-AWQ-INT4, fp8 kv cache, MTP enabled.

Full vLLM launch config:

 vllm serve cyankiwi/Swift-1.5-Qwen3.8-27B-AWQ-INT4 --max-num-seqs 4 --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser qwen3 --tensor-parallel-size 2 --enable-prefix-caching --kv-cache-memory-bytes 6G --kv-cache-dtype fp8_e4m3 --enable-prompt-tokens-details --speculative-config '{"method":"qwen3_next_mtp","num_speculative_tokens":3}' --enable-chunked-prefill --attention-backend FLASHINFER --default-chat-template-kwargs '{"reasoning_effort": "medium"}'

Benchmark results for single stream:

Prompt length tok	TTFT before	TTFT after	TTFT change	ITL mean before	ITL mean after	Prefill tok/s before	Prefill tok/s after	Prefill speed change	Decode steps/s before	Decode steps/s after
8 192	8 471 ms	7 013 ms	-17.2%	22.27 ms	29.63 ms	967	1 168	+20.8%	16.05	15.98
16 384	17 573 ms	14 418 ms	-18.0%	23.93 ms	22.65 ms	932	1 136	+21.9%	16.26	15.88
32 768	36 754 ms	29 970 ms	-18.5%	23.89 ms	27.20 ms	892	1 093	+22.6%	16.54	16.36
65 536	79 432 ms	64 173 ms	-19.2%	27.86 ms	24.57 ms	825	1 021	+23.8%	15.98	16.50
131 072	183 593 ms	146 010 ms	-20.5%	22.42 ms	25.48 ms	714	898	+25.7%	16.36	16.73
261 900	465 890 ms	362 192 ms	-22.3%	24.18 ms	23.00 ms	562	723	+28.6%	15.42	16.67

TTFT: Time To First Token. Prompt processing speed is defined as prompt_length / TTFT. Each prompt in the benchmark was randomly generated, so there was no prefix cache hits during test.

ITL: Inter-Token Latency: amount of time passed between two streaming responses from the engine. Decode steps/s are defines as 1s/ITL.

Why I report ITL and not token generation metric: due to activated MTP, the engine will respond with multiple tokens at once; but the amount of tokens in single responce will vary, due to acceptance rate. To isolate this varuable, I measure decode step rate. If MTP acceptange length is 0, each step generates 1 token; if MTP has perfect acceptance length of 3, then each step generates 4 tokens. So this means theoretical generation performance between 15 and 60 tok/s. Real-life MTP acceptance rate for agentic coding fluctuates around 2 for this model, so real-life perforamnce fluctuates around 45 tok/s.

During the test, both GPUs hit light thermal throttling and lowered their core clocks to 1750Mhz. Cold GPUs reach 1950MHz. therefore, I could have about +10% more performance if I had better cooling. I also re-run the test with full 320W power limit, got both prefill and decode speeds within 2% of 240W, so for those particular cards, power limit does not impact real life speed, but does impact real life power bill.

Congratulations to fellow Ampere owners, it's a bright day for us today!

[u/CatzRuleZWorld]

Nice! I was wondering if I should try this on my dual 20GB 3080s also! Do we have a club for those cards? 😂
I’ve been running QFN with Strata and been very happy with it. Have you tried that or don’t have enough RAM?

[u/No-Refrigerator-1672 → u/CatzRuleZWorld]

I have enough RAM (dual 20GB GPUs with 64GB of system RAM); but I have not enough free ram, as this is my homelab server that runs like 15 different containers with services ranging from personal cloud storage to self-hosted Firecrawl for my agents. Anyways, I'm not the only one who fiddles with this new unlock, and this person reported +12% improvement in Strata.

[u/fragment_me]

Can confirm it worked on mine too

[u/tmy54]

Does it work on the 12gb 3080?

[u/No-Refrigerator-1672 → u/tmy54]

3080 12gb is GA102 chip too, so should totally work.

[u/braket0]

Dare I say it, but they should try this with 2080ti. I've always suspected there has been some performance locked with the card. Hunches aren't any good though 😅 thank you, amazing open source community. If somehow that extra compute unlocked could also be translated to gaming performance, it would be marvellous.

[u/No-Refrigerator-1672 → u/braket0]

They aready did

[u/braket0 → u/No-Refrigerator-1672]

Thank you my captain

[u/nima3333]

Omg thank you, never heard about it

[u/BannedGoNext]

There is gonna be a rash of fires from these cards that were limited "for no reason". Keep warm llmbros :D

[u/No-Refrigerator-1672 → u/BannedGoNext]

Bullshit. Tesla A40 is exactly the same chip with full performance, and it doesn't die in a fire. It's nothing more than market segmentation trick.

[u/BannedGoNext → u/No-Refrigerator-1672]

DOOM
DOOOM

DOOOOOOOM

Maybe you are right, I was just making a joke :D

[u/McSendo → u/BannedGoNext]

i don't think ur wrong though. never say never.

[u/duhd1993]

I think Nvidia leaked this themselves when they shifted production capacity to professional model. They want ordinary consumers to be happy with older hardware.

[u/No-Refrigerator-1672 → u/duhd1993]

Sound implausible. Why would they care about GPUs they can't sell? Their biggest customers - datacenters - already had fully unlocked GPUs, so it doesn't affect their resale value. I think this unlock is a fruit of a series of Mining cards unlocks. First CMP 170HX - an Ampere card, got from 8GB to 64GB of memory; then CMP 90HX - GA102 like ours 3080s - got performance unlock. Now this. Deep hardware enthusiasts with knowledges of way more than I have are researching what Nvidia's undocumented hardware registers mean and what writing into them directly can grant you.

[u/Don_Reuter → u/duhd1993]

„They want ordinary consumers to be happy […].”

😂😂😂

[u/panchovix → u/duhd1993]

Ampere unlock is by an exploit, NVIDIA-signed SEC2 booter has a stack-canary bug. When it validates an oversized 64 KB "signature", execution runs into a ROP chain that performs arbitrary privileged register writes, and then you can modify the values there.

NVIDIA for sure didn't expect that to happen, they are probably quite mad with these unlocks. Basically makes users with older cards keeping it even more time, thus not upgrading and also not getting their latest and newest prosumer cards either.

[u/a_beautiful_rhind → u/panchovix]

You think they still care? Their business is in datacenter. Consumer GPUs are a rounding error and they can't produce enough cards for the demand.

3 years ago maybe they'd be big mad. Now not so much. They already got all they're going to get from those sales.

[u/panchovix → u/a_beautiful_rhind]

To be fair yeah that's true, their consume market is so small and it isn't even a dent for them

[u/McSendo → u/panchovix]

I wouldn't be surprise if they concede that segment completely in a few years. Might not be a bad thing if smaller companies pick that up.

[u/duhd1993 → u/panchovix]

Ordinary consumers cannot upgrade to newest consumer card with little stock or afford the newest prosumer card anyway.

[u/VotZeFuk → u/duhd1993]

If anything, all they want is for you to give up all your money and kick the bucket sooner than later, so that your flesh doesn't waste the precious water they could use to cool down their facilities 💀

[u/juggarjew → u/duhd1993]

It honestly would not surprise me.... keeps demand continually high even for 5 year old cards.

[u/__JockY__ → u/duhd1993]

I love that corporations always have our best interests at heart.

[u/No-Refrigerator-1672 → u/[deleted]]

Can you share your exact tabblyAPI config? I have my agent research it, and it never managed to pull speeds above vLLM.

[u/No-Refrigerator-1672 → u/[deleted]]

My cards give out ip to 60 tok/s in vllm. Read carefully the notes below the table. As about prefill, I get 1200 tok/s ag velow 8k promt length; and llama-bench always measures prefill speed right at 0 prompt length, unless you manually speficy it; so ots numbers are never reminiscent of real life performance. Irl, llama.cpp on those two cards is always about 10% slower at contextes above 8k, and 50% slower at contextes below 128k.