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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2401252-NE-RTX4070SU41
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: 1 - Model: ResNet-50
batches/sec > Higher Is Better
PyTorch 2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
RTX 4070 SUPER . 201.94 |======================================================
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: 32 - Model: ResNet-50
batches/sec > Higher Is Better
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-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: 32 - Model: ResNet-152
batches/sec > Higher Is Better
RTX 4070 SUPER . 195.39 |======================================================
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: 64 - Model: ResNet-152
batches/sec > Higher Is Better
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-152
batches/sec > Higher Is Better
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: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
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: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
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: 512 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
RTX 4070 SUPER . 103.57 |======================================================
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: Memory Bandwidth Coalesced Write
GB/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 455.01 |===============================================
ProjectPhysX OpenCL-Benchmark 1.2
Operation: FP64 Compute
TFLOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 0.621 |================================================
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: INT64 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 4.214 |================================================
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: INT16 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 17.17 |================================================
ProjectPhysX OpenCL-Benchmark 1.2
Operation: INT8 Compute
TIOPs/s > Higher Is Better
NVIDIA RTX 4070 SUPER . 14.31 |================================================