NVIDIA GeForce RTX 3090

AMD Ryzen 9 7950X 16-Core testing with a ASUS TUF GAMING X670E-PLUS WIFI (0613 BIOS) and Gigabyte NVIDIA GeForce RTX 4090 24GB on Ubuntu 22.04 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 2210138-NE-2112069PT61
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BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C++ Boost Tests 2 Tests
CPU Massive 5 Tests
Creator Workloads 6 Tests
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HPC - High Performance Computing 8 Tests
Machine Learning 5 Tests
Multi-Core 8 Tests
NVIDIA GPU Compute 31 Tests
OpenCL 6 Tests
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Vulkan Compute 8 Tests
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RTX 3090
December 05 2021
  2 Hours, 29 Minutes
NVIDIA RTX 3090
December 05 2021
  7 Hours, 31 Minutes
NVIDIA 3090
December 06 2021
  2 Hours, 25 Minutes
RTX 4090
October 13 2022
  6 Hours, 50 Minutes
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  4 Hours, 49 Minutes

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NVIDIA GeForce RTX 3090 Suite 1.0.0 System Test suite extracted from NVIDIA GeForce RTX 3090. pts/shoc-1.2.0 -opencl -benchmark MaxFlops Target: OpenCL - Benchmark: Max SP Flops pts/vkfft-1.1.0 pts/etlegacy-1.2.0 +set r_customwidth 3840 +set r_customheight 2160 Resolution: 3840 x 2160 pts/vkpeak-1.0.2 fp64-vec4 pts/vkpeak-1.0.2 int16-vec4 pts/vkpeak-1.0.2 int16-scalar pts/vkpeak-1.0.2 int32-vec4 pts/vkpeak-1.0.2 int32-scalar pts/vkpeak-1.0.2 fp64-scalar pts/vkpeak-1.0.2 fp16-vec4 pts/vkpeak-1.0.2 fp16-scalar pts/vkpeak-1.0.2 fp32-vec4 pts/vkpeak-1.0.2 fp32-scalar pts/lczero-1.6.0 -b opencl Backend: OpenCL pts/octanebench-1.3.0 Total Score pts/warsow-1.6.0 +vid_width 1920 +vid_height 1080 Resolution: 1920 x 1080 pts/fahbench-1.0.2 pts/warsow-1.6.0 +vid_width 1920 +vid_height 1200 Resolution: 1920 x 1200 pts/warsow-1.6.0 +vid_width 2560 +vid_height 1440 Resolution: 2560 x 1440 pts/warsow-1.6.0 +vid_width 3840 +vid_height 2160 Resolution: 3840 x 2160 pts/luxcorerender-1.3.0 DLSC/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: DLSC - Acceleration: GPU pts/blender-3.0.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Barbershop - Compute: CUDA pts/luxcorerender-1.3.0 LuxCore2.1Benchmark/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: LuxCore Benchmark - Acceleration: GPU pts/v-ray-1.3.0 -m vray-gpu-rtx Mode: NVIDIA RTX GPU pts/v-ray-1.3.0 -m vray-gpu-cuda Mode: NVIDIA CUDA GPU pts/luxcorerender-1.3.0 OrangeJuice/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Orange Juice - Acceleration: GPU pts/indigobench-1.1.0 --gpuonly --scenes bedroom Acceleration: OpenCL GPU - Scene: Bedroom pts/indigobench-1.1.0 --gpuonly --scenes supercar Acceleration: OpenCL GPU - Scene: Supercar pts/luxcorerender-1.3.0 DanishMood/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Danish Mood - Acceleration: GPU pts/namd-cuda-1.1.1 ATPase Simulation - 327,506 Atoms pts/blender-3.0.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Barbershop - Compute: NVIDIA OptiX pts/unvanquished-1.6.0 +set r_customWidth 2560 +set r_customHeight 1440 +preset presets/graphics/ultra.cfg Resolution: 2560 x 1440 - Effects Quality: Ultra pts/ncnn-1.3.0 Target: Vulkan GPU - Model: regnety_400m pts/ncnn-1.3.0 Target: Vulkan GPU - Model: squeezenet_ssd pts/ncnn-1.3.0 Target: Vulkan GPU - Model: yolov4-tiny pts/ncnn-1.3.0 Target: Vulkan GPU - Model: resnet50 pts/ncnn-1.3.0 Target: Vulkan GPU - Model: alexnet pts/ncnn-1.3.0 Target: Vulkan GPU - Model: resnet18 pts/ncnn-1.3.0 Target: Vulkan GPU - Model: vgg16 pts/ncnn-1.3.0 Target: Vulkan GPU - Model: googlenet pts/ncnn-1.3.0 Target: Vulkan GPU - Model: blazeface pts/ncnn-1.3.0 Target: Vulkan GPU - Model: efficientnet-b0 pts/ncnn-1.3.0 Target: Vulkan GPU - Model: mnasnet pts/ncnn-1.3.0 Target: Vulkan GPU - Model: shufflenet-v2 pts/ncnn-1.3.0 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 pts/ncnn-1.3.0 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.3.0 Target: Vulkan GPU - Model: mobilenet pts/blender-3.0.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Pabellon Barcelona - Compute: CUDA pts/clpeak-1.0.1 --compute-dp OpenCL Test: Double-Precision Double pts/xonotic-1.5.2 +vid_width 3840 +vid_height 2160 +exec effects-ultimate.cfg Resolution: 3840 x 2160 - Effects Quality: Ultimate pts/blender-3.0.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: BMW27 - Compute: CUDA pts/unvanquished-1.6.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/ultra.cfg Resolution: 1920 x 1080 - Effects Quality: Ultra pts/realsr-ncnn-1.0.0 -s 4 -x Scale: 4x - TAA: Yes pts/xonotic-1.5.2 +vid_width 3840 +vid_height 2160 +exec effects-ultra.cfg Resolution: 3840 x 2160 - Effects Quality: Ultra pts/unvanquished-1.6.0 +set r_customWidth 3840 +set r_customHeight 2160 +preset presets/graphics/ultra.cfg Resolution: 3840 x 2160 - Effects Quality: Ultra pts/unvanquished-1.6.0 +set r_customWidth 1920 +set r_customHeight 1200 +preset presets/graphics/ultra.cfg Resolution: 1920 x 1200 - Effects Quality: Ultra pts/unvanquished-1.6.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/high.cfg Resolution: 1920 x 1080 - Effects Quality: High pts/unvanquished-1.6.0 +set r_customWidth 3840 +set r_customHeight 2160 +preset presets/graphics/high.cfg Resolution: 3840 x 2160 - Effects Quality: High pts/unvanquished-1.6.0 +set r_customWidth 2560 +set r_customHeight 1440 +preset presets/graphics/high.cfg Resolution: 2560 x 1440 - Effects Quality: High pts/unvanquished-1.6.0 +set r_customWidth 1920 +set r_customHeight 1200 +preset presets/graphics/high.cfg Resolution: 1920 x 1200 - Effects Quality: High pts/xonotic-1.5.2 +vid_width 3840 +vid_height 2160 +exec effects-high.cfg Resolution: 3840 x 2160 - Effects Quality: High pts/vkresample-1.0.0 -u 2 -p 1 Upscale: 2x - Precision: Double pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sCOPY pts/unvanquished-1.6.0 +set r_customWidth 2560 +set r_customHeight 1440 +preset presets/graphics/medium.cfg Resolution: 2560 x 1440 - Effects Quality: Medium pts/unvanquished-1.6.0 +set r_customWidth 3840 +set r_customHeight 2160 +preset presets/graphics/medium.cfg Resolution: 3840 x 2160 - Effects Quality: Medium pts/unvanquished-1.6.0 +set r_customWidth 1920 +set r_customHeight 1200 +preset presets/graphics/medium.cfg Resolution: 1920 x 1200 - Effects Quality: Medium pts/unvanquished-1.6.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/medium.cfg Resolution: 1920 x 1080 - Effects Quality: Medium pts/blender-3.0.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Fishy Cat - Compute: CUDA pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-TT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sCOPY pts/blender-3.0.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Classroom - Compute: CUDA pts/xonotic-1.5.2 +vid_width 3840 +vid_height 2160 +exec effects-low.cfg Resolution: 3840 x 2160 - Effects Quality: Low pts/blender-3.0.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Fishy Cat - Compute: NVIDIA OptiX pts/paraview-1.2.0 manyspheres.py -s 100 -r 726 -f 600 -v 3840,2160 Test: Many Spheres - Resolution: 3840 x 2160 pts/paraview-1.2.0 manyspheres.py -s 100 -r 726 -f 600 -v 1920,1080 Test: Many Spheres - Resolution: 1920 x 1080 pts/paraview-1.2.0 manyspheres.py -s 100 -r 726 -f 600 -v 1920,1200 Test: Many Spheres - Resolution: 1920 x 1200 pts/paraview-1.2.0 manyspheres.py -s 100 -r 726 -f 600 -v 2560,1440 Test: Many Spheres - Resolution: 2560 x 1440 pts/shoc-1.2.0 -opencl -benchmark DeviceMemory Target: OpenCL - Benchmark: Texture Read Bandwidth pts/blender-3.0.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Pabellon Barcelona - Compute: NVIDIA OptiX pts/blender-3.0.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Classroom - Compute: NVIDIA OptiX pts/etlegacy-1.2.0 +set r_customwidth 2560 +set r_customheight 1440 Resolution: 2560 x 1440 pts/blender-3.0.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: BMW27 - Compute: NVIDIA OptiX pts/etlegacy-1.2.0 +set r_customwidth 1920 +set r_customheight 1080 Resolution: 1920 x 1080 pts/etlegacy-1.2.0 +set r_customwidth 1920 +set r_customheight 1200 Resolution: 1920 x 1200 pts/vkresample-1.0.0 -u 2 -p 0 Upscale: 2x - Precision: Single pts/paraview-1.2.0 waveletcontour.py -d 256 -f 600 -v 3840,2160 Test: Wavelet Contour - Resolution: 3840 x 2160 pts/hashcat-1.1.1 -m 1700 Benchmark: SHA-512 pts/paraview-1.2.0 waveletvolume.py -d 256 -f 600 -v 3840,2160 Test: Wavelet Volume - Resolution: 3840 x 2160 pts/paraview-1.2.0 waveletcontour.py -d 256 -f 600 -v 2560,1440 Test: Wavelet Contour - Resolution: 2560 x 1440 pts/paraview-1.2.0 waveletcontour.py -d 256 -f 600 -v 1920,1200 Test: Wavelet Contour - Resolution: 1920 x 1200 pts/paraview-1.2.0 waveletcontour.py -d 256 -f 600 -v 1920,1080 Test: Wavelet Contour - Resolution: 1920 x 1080 pts/hashcat-1.1.1 -m 100 Benchmark: SHA1 pts/hashcat-1.1.1 -m 0 Benchmark: MD5 pts/hashcat-1.1.1 -m 6211 Benchmark: TrueCrypt RIPEMD160 + XTS pts/redshift-1.0.1 pts/luxcorerender-1.3.0 RainbowColorsAndPrism/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Rainbow Colors and Prism - Acceleration: GPU pts/paraview-1.2.0 waveletvolume.py -d 256 -f 600 -v 2560,1440 Test: Wavelet Volume - Resolution: 2560 x 1440 pts/paraview-1.2.0 waveletvolume.py -d 256 -f 600 -v 1920,1200 Test: Wavelet Volume - Resolution: 1920 x 1200 pts/paraview-1.2.0 waveletvolume.py -d 256 -f 600 -v 1920,1080 Test: Wavelet Volume - Resolution: 1920 x 1080 pts/realsr-ncnn-1.0.0 -s 4 Scale: 4x - TAA: No pts/rodinia-1.3.1 OCL_PARTICLEFILTER Test: OpenCL Particle Filter pts/hashcat-1.1.1 -m 11600 Benchmark: 7-Zip pts/arrayfire-1.1.0 cg_opencl Test: Conjugate Gradient OpenCL pts/shoc-1.2.0 -opencl -benchmark BusSpeedReadback Target: OpenCL - Benchmark: Bus Speed Readback pts/plaidml-1.0.4 --no-fp16 --no-train densenet201 OPENCL FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL pts/waifu2x-ncnn-1.0.0 -s 2 -n 3 -x Scale: 2x - Denoise: 3 - TAA: Yes pts/plaidml-1.0.4 --no-fp16 --train mobilenet OPENCL FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL pts/cl-mem-1.0.1 COPY Benchmark: Copy pts/cl-mem-1.0.1 READ Benchmark: Read pts/cl-mem-1.0.1 WRITE Benchmark: Write pts/shoc-1.2.0 -opencl -benchmark GEMM Target: OpenCL - Benchmark: GEMM SGEMM_N pts/mandelgpu-1.3.1 0 1 OpenCL Device: GPU pts/shoc-1.2.0 -opencl -benchmark S3D Target: OpenCL - Benchmark: S3D pts/shoc-1.2.0 -opencl -benchmark BusSpeedDownload Target: OpenCL - Benchmark: Bus Speed Download pts/shoc-1.2.0 -opencl -benchmark Triad Target: OpenCL - Benchmark: Triad pts/clpeak-1.0.1 --compute-integer OpenCL Test: Integer Compute INT pts/shoc-1.2.0 -opencl -benchmark FFT Target: OpenCL - Benchmark: FFT SP pts/waifu2x-ncnn-1.0.0 -s 2 -n 3 Scale: 2x - Denoise: 3 - TAA: No pts/plaidml-1.0.4 --fp16 --no-train mobilenet OPENCL FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/shoc-1.2.0 -opencl -benchmark Reduction Target: OpenCL - Benchmark: Reduction pts/shoc-1.2.0 -opencl -benchmark MD5Hash Target: OpenCL - Benchmark: MD5 Hash pts/plaidml-1.0.4 --no-fp16 --no-train mobilenet OPENCL FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/plaidml-1.0.4 --no-fp16 --no-train imdb_lstm OPENCL FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL pts/clpeak-1.0.1 --compute-sp OpenCL Test: Single-Precision Float pts/clpeak-1.0.1 --global-bandwidth OpenCL Test: Global Memory Bandwidth pts/financebench-1.1.1 Black-Scholes/OpenCL/blackScholesAnalyticEngine.exe Benchmark: Black-Scholes OpenCL pts/libplacebo-1.0.0 pts/neatbench-1.0.4 gpu Acceleration: GPU pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 100 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 1000 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 200 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 100 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100 pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 1000 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000 pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 200 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200 pts/mixbench-1.1.1 mixbench-ocl-ro GIOPS Backend: OpenCL - Benchmark: Integer pts/gromacs-1.6.0 cuda-build water-cut1.0_GMX50_bare/1536 Implementation: NVIDIA CUDA GPU - Input: water_GMX50_bare pts/betsy-1.0.0 --codec=etc2_rgb --quality=2 Codec: ETC2 RGB - Quality: Highest pts/betsy-1.0.0 --codec=etc1 --quality=2 Codec: ETC1 - Quality: Highest pts/mixbench-1.1.1 mixbench-cuda-ro SPGFLOPS Backend: NVIDIA CUDA - Benchmark: Single Precision pts/mixbench-1.1.1 mixbench-cuda-ro DPGFLOPS Backend: NVIDIA CUDA - Benchmark: Double Precision pts/mixbench-1.1.1 mixbench-cuda-ro HPGFLOPS Backend: NVIDIA CUDA - Benchmark: Half Precision pts/mixbench-1.1.1 mixbench-ocl-ro SPGFLOPS Backend: OpenCL - Benchmark: Single Precision pts/mixbench-1.1.1 mixbench-ocl-ro DPGFLOPS Backend: OpenCL - Benchmark: Double Precision pts/mixbench-1.1.1 mixbench-cuda-ro GIOPS Backend: NVIDIA CUDA - Benchmark: Integer