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The open-source project gpu-unlock 1.0.0 provides an FP/BF16 instruction issue rate unlock for Nvidia 3000 series graphics cards. According to a report dated October 24, 2026, this Linux kernel module can complete the unlock before the NVIDIA driver binds to the graphics card, doubling the FP/BF16 FMA instruction issue rate of GA102, GA103, GA104, and GA106 graphics cards to bring them to professional-card levels, thus eliminating the need to manually patch after every driver update. In measured tests, the RTX 3090 Ti's BF16 rose from 87.50 TFLOPS to 157.41 TFLOPS, FP16 from 87.46 to 118.39 TFLOPS, and TF32 from 42.58 to 82.61 TFLOPS. Subsequent reports stated that the tool lifts the restriction by rewriting the speed select register, with no need to flash the VBIOS or modify the driver; the RTX 3090 Ti's BF16 improves by about 80%, ComfyUI image generation throughput improves by 56% to 59%, and the RTX 3090's prompt prefill throughput under vLLM improves by about 33%, but the Decode stage of per-token generation sees almost no improvement due to VRAM bandwidth limits. This modification is not officially supported by Nvidia, and you must bear the power consumption, cooling, and warranty risks yourself.
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gpu-unlock 1.0.0 provides FP/BF16 unlock for Nvidia 3000 series
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Semiconductor Industry Observer
Open-source tool GPU Unlock unlocks hidden compute power in RTX 30 series graphics cards
The open-source tool GPU Unlock, developed by GitHub user Zagitta, uses a Linux kernel module to rewrite the speed select register before the driver loads, removing NVIDIA's restriction on tensor core instruction issue rates on consumer Ampere graphics cards, without the need to flash the VBIOS or modify the driver. In measured tests, the BF16 compute power of the RTX 3090 Ti rose from 87.5 TFLOPS to 157.4 TFLOPS, an increase of about 80%, and ComfyUI image generation throughput increased by 56% to 59%; for the RTX 3090 under vLLM, prompt prefill throughput improved by about 33%, but the Decode stage of token-by-token generation showed almost no improvement due to memory bandwidth limitations. The project supports GA102, GA103, GA104, and GA106 cores, and is a firmware-level modification not officially supported by NVIDIA, so users must bear the power consumption, cooling, and warranty risks themselves.
36Kr · AI
Open-source project unlocks hidden compute power in NVIDIA RTX graphics cards, RTX 4090 specific Tensor Core throughput doubles
An open-source project on GitHub unlocks rate limits on NVIDIA GeForce graphics cards for specific Tensor Core operations by modifying register configurations during the GPU boot phase; the RTX 4090's FP16 input, FP32 accumulate throughput rate rises from 165.6 TFLOPS to 331.6 TFLOPS. The RTX 3090 Ti, 3080, 3070, 3060, and RTX 2080 Ti also show gains of roughly 60% to 90%, with no need to flash the BIOS, and the original NVIDIA driver can run as usual. However, the actual cuBLAS matrix multiplication increase narrows to about 12% to 34%, and per-token generation speed shows no obvious change.
Oct 24
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gpu-unlock: Unlocking the FP/BF16 instruction issue rate of Nvidia 3000 series graphics cards
The Linux kernel module gpu-unlock 1.0.0 can double the FP/BF16 FMA instruction issue rate of GA102, GA103, GA104, and GA106 graphics cards, bringing them up to professional card levels. On the 3090 Ti, BF16 rises from 87.50 TFLOPS to 157.41 TFLOPS, FP16 from 87.46 to 118.39 TFLOPS, and TF32 from 42.58 to 82.61 TFLOPS. The module completes the unlock before the NVIDIA driver binds the graphics card, so there is no need to manually patch after each driver update.
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