Ada GPU Unlock Lifts RTX 4090 Tensor Throughput to 331 TF/s
A consumer RTX 4090 can now deliver FP16/BF16 tensor throughput comparable to far more expensive pro cards, changing the cost math for small-scale deep learning and inference. The price is experimental firmware, initramfs-level setup, and a real chance that a driver update, Secure Boot policy, or unverified board breaks the unlock.
gpu-unlock-ada loads before NVIDIA's driver, a kernel module that rewrites SM speed-selector registers on consumer Ada cards. On an RTX 4090 it raises FP16/FP32 and BF16/FP32 tensor throughput from about 165 TF/s to 331 TF/s; a measured RTX 4070 Ti SUPER at a 240W power limit goes from 95.0 to 189.9 TF/s. INT8 and dp4a operators stay at baseline, so the change is limited to the tensor path the speed selector controls.
Only RTX 4090, RTX 4070 Ti SUPER, and RTX 4060 Ti 16GB are verified. The module must be built into initramfs and enabled with a gpu_unlock.targets kernel parameter; AD103 and AD106 cards need an exact PCI address plus an experimental flag. Firmware assets come from NVIDIA's 610.43.03 driver source with SHA-256 verification, and the unlocked state survives a PCIe function-level reset. A 4096^3 BF16 GEMM shows no gain, which makes the 2x headline workload-dependent, and the first install requires a cold boot because WPR2 may block a warm reboot.
The selective result is the tell: INT8 and dp4a stay flat while FP16/BF16 doubles, exactly what a speed-selector override should do.
Basing the unlock on NVIDIA's own signed Booter assets makes it reproducible and auditable, but also couples it to NVIDIA's firmware pipeline; a driver source change, Secure Boot policy, or firmware update can break the signature chain.
Shape-dependent GEMM results, including a 4096^3 BF16 case with no gain, mean the 2x headline cannot be used to plan capacity; only per-shape benchmarks can.
The star count and open issues together suggest early adopters are already running experimental firmware on production-class GPUs before long-term stability is known.