RTX 4070 SUPER
Intel Core i9-13900K testing with a ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS) and ASUS NVIDIA GeForce RTX 4070 SUPER 12GB on EndeavourOS rolling via the Phoronix Test Suite.


NVIDIA RTX 4070 SUPER: 

	Processor: Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads), Motherboard: ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: 4001GB Seagate ZP4000GP304001, Graphics: ASUS NVIDIA GeForce RTX 4070 SUPER 12GB, Audio: Realtek ALC1220, Monitor: ARZOPA, Network: Intel I226-V + Intel Device 7a70

	OS: EndeavourOS rolling, Kernel: 6.7.1-arch1-1 (x86_64), Desktop: KDE Plasma 5.27.10, Display Server: X Server 1.21.1.11, Display Driver: NVIDIA 550.40.07, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.74, Compiler: GCC 13.2.1 20230801, File-System: ext4, Screen Resolution: 1920x1080

RTX 4070 SUPER: 

	Processor: Intel Core i9-13900K @ 5.50GHz (24 Cores / 32 Threads), Motherboard: ASUS TUF GAMING Z790-PRO WIFI (1401 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: 4001GB Seagate ZP4000GP304001, Graphics: ASUS NVIDIA GeForce RTX 4070 SUPER 12GB, Audio: Realtek ALC1220, Monitor: ARZOPA, Network: Intel I226-V + Intel Device 7a70

	OS: EndeavourOS rolling, Kernel: 6.7.1-arch1-1 (x86_64), Desktop: KDE Plasma 5.27.10, Display Server: X Server 1.21.1.11, Display Driver: NVIDIA 550.40.07, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.74, Compiler: GCC 13.2.1 20230801, File-System: ext4, Screen Resolution: 1920x1080


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
RTX 4070 SUPER . 103.57 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
RTX 4070 SUPER . 103.17 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
RTX 4070 SUPER . 102.60 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
RTX 4070 SUPER . 106.37 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152
batches/sec > Higher Is Better
RTX 4070 SUPER . 194.58 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50
batches/sec > Higher Is Better
RTX 4070 SUPER . 504.27 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
RTX 4070 SUPER . 195.39 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
RTX 4070 SUPER . 507.45 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
RTX 4070 SUPER . 509.45 |======================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
RTX 4070 SUPER . 201.94 |======================================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: Memory Bandwidth Coalesced Write
GB/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 455.01 |===============================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: Memory Bandwidth Coalesced Read
GB/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 464.86 |===============================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: INT8 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 14.31 |================================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: INT16 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 17.17 |================================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: INT32 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 19.89 |================================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: INT64 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 4.214 |================================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: FP32 Compute
TFLOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 38.59 |================================================


ProjectPhysX OpenCL-Benchmark 1.2
Operation: FP64 Compute
TFLOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 0.621 |================================================


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better


PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better