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NVIDIA
nvidia.com › en-us › geforce › news › nvidia-frameview-power-and-performance-benchmarking-app-download
FrameView Performance and Power Benchmarking App: Free Download Available Now | GeForce News | NVIDIA
To date, no single tool or app has accurately delivered these results, which is why we’ve created FrameView, an all-in-one benchmarking app that you can download and use for free.
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NVIDIA Developer
developer.nvidia.com › nvidia-hpc-benchmarks-downloads
nvidia-hpc-benchmarks 26.02 Downloads | NVIDIA Developer
Click on the green buttons that describe your target platform. Only supported platforms will be shown. By downloading and using the software, you agree to fully comply with the terms and conditions of the NVIDIA Software License Agreement.
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NVIDIA
catalog.ngc.nvidia.com › orgs › nvidia › containers › hpc-benchmarks
NVIDIA HPC-Benchmarks - NGC Catalog
The HPC benchmarks package stores open-source code inside the container at /workspace/open_source/, in addition to the DLFW open source code. In addition to NVIDIA Optimized Frameworks 26.02 container images, the hpc-benchmarks:26.02 container image is provided with the following packages embedded:
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NVIDIA
nvidia.com › en-us › geforce › technologies › frameview
Download FrameView App | NVIDIA
Benchmark your GPU’s power, frames per second (FPS), and performance per watt with the free FrameView app from NVIDIA GeForce.
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NVIDIA
docs.nvidia.com › nvidia-hpc-benchmarks
NVIDIA HPC Benchmarks — NVIDIA HPC Benchmarks
NVIDIA HPC-Benchmarks collection provides four benchmarks (HPL, HPL-MxP, HPCG, and STREAM) widely used in the HPC community optimized for performance on NVIDIA accelerated HPC systems.
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Guru3D
guru3d.com › home › files › categories › benchmarks & demo's
www.guru3d.com - Benchmarks & Demo's
Benchmarks & Demo's 179 Updated 2021-04-19 18:26 by Hilbert Hagedoorn 0 · Download the NVIDIA Unreal Engine 4 RTX & DLSS Demo. this is a raytracing and DLSS showcase demo. Raytracing also works in AMD Radeon cards.
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Unigine
benchmark.unigine.com › heaven
Heaven benchmark
NVIDIA GeForce 8xxx and higher · Video memory: 512 MB · Disk space: 1 GB · Operating system · MS Windows XP / Vista / 7 / 8 / 10 / 11 · Linux (proprietary video drivers required) Mac OS X 10.8+ (Mountain Lion) Heaven Benchmark is a ...
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benchmarks UL
benchmarks.ul.com › 3dmark
3DMark benchmark for Windows, Android and iOS
Benchmark your PC, tablet and smartphone with 3DMark, The Gamer's Benchmark. Free download, start benchmarking today.
Find elsewhere
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NVIDIA
nvidia.com › en-us › data-center › performance-benchmarking
Optimize AI Workload Performance | NVIDIA Performance Benchmarking
April 28, 2026 - Achieve higher performance of NVIDIA AI infrastructure and AI workloads with a suite of tools, recipes, and services. ... Optimize your AI workload with performance recipes, and quickly set up and run standardized benchmarking methodologies in your environment.
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PassMark
videocardbenchmark.net
PassMark Software - Video Card (GPU) Benchmark Charts
In the case of these Video Card Benchmarks there are several factors to consider, such as different system setups the Video Cards are running under and the possibility that users have overclocked their systems.... [ Learn more about the graphs] Download and install the latest version of PerformanceTest.
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NVIDIA
nvidia.com › en-us › geforce › community › demos
Download NVIDIA Tech Demos | NVIDIA Cool Stuff
Justice is one of China’s most ... demo NVIDIA RTX Ray-Traced Reflections, Shadows, and Caustics are demonstrated, along with Deep Learning Super Sampling. ... Deep Learning Super-Sampling increases performance significantly in FFXV, whilst simultaneously improving image quality. Learn more, see the improvements, and download the benchmark ...
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GitHub
github.com › NVIDIA › dgxc-benchmarking
GitHub - NVIDIA/dgxc-benchmarking: DGXC Benchmarking provides recipes in ready-to-use templates for evaluating performance of specific AI use cases across hardware and software combinations. · GitHub
curl -L https://ngc.nvidia.com/downloads/ngccli_arm64.zip -o ngccli_arm64.zip unzip -q ngccli_arm64.zip -d $HOME/.local/bin rm ngccli_arm64.zip export PATH=$HOME/.local/bin/ngc-cli:$PATH ngc config set
Starred by 92 users
Forked by 28 users
Languages   Python 74.2% | Shell 25.6% | Go Template 0.2%
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GitHub
github.com › NVIDIA › nvbench
GitHub - NVIDIA/nvbench: CUDA Kernel Benchmarking Library · GitHub
CUDA Kernel Benchmarking Library. Contribute to NVIDIA/nvbench development by creating an account on GitHub.
Starred by 875 users
Forked by 109 users
Languages   Cuda 55.2% | Python 19.6% | C++ 14.4% | CMake 4.9% | Shell 4.2% | PowerShell 1.7%
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UserBenchmark
gpu.userbenchmark.com › Software
GPU Speed Test Tool - Compare Your PC - UserBenchmark
Free benchmarking software. Compare results with other users and see which parts you can upgrade together with the expected performance improvements.
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NVIDIA
docs.nvidia.com › nvidia-hpc-benchmarks › STREAM_Benchmark.html
NVIDIA STREAM Benchmark — NVIDIA HPC Benchmarks
stream_test executable. NVIDIA STREAM benchmark for NVIDIA Grace CPU with double precision elements
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GitHub
github.com › NVIDIA-AI-IOT › jetson_benchmarks
GitHub - NVIDIA-AI-IOT/jetson_benchmarks: Jetson Benchmark · GitHub
For benchmark results on all NVIDIA Jetson Products; please have a look at NVIDIA jetson_benchmark webpage · Following scripts are included: Installation requirements for running benchmark script (install_requirements.sh) CSV files containing parameters (benchmark_csv folder) Download Model (utils/download_models.py) Running Benchmark Script (benchmarks.py) JetPack 4.4+ TensorRT 7+ git clone https://github.com/NVIDIA-AI-IOT/jetson_benchmarks.git cd jetson_benchmarks mkdir models # Open folder to store models (Optional) sudo sh install_requirements.sh Note: All libraries will be installed for python3 ·
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Forked by 77 users
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Reddit
reddit.com › r/nvidia › i built a benchmark tool for nvidia gpus running ai workloads
r/nvidia on Reddit: I built a benchmark tool for NVIDIA GPUs running AI workloads
April 30, 2025 -

Hey.

I wanted to share a free, open-source GPU benchmark tool I built specifically for measuring how NVIDIA GPUs perform under AI workloads (Stable Diffusion). Unlike typical benchmarks that focus on gaming performance, this tests how your card handles machine learning tasks.

What it measures:

  • Processing speed: How many images your GPU can generate in 5 minutes

  • Temperature monitoring: Both peak and average temps during sustained AI workload

  • Power draw: Precise wattage consumption under load

  • Other technical specs: Like VRAM, platform and more

Some interesting findings from our current data:

  • RTX 4090 generated 199 images (318W, 55°C max)

  • RTX 3090 generated 116 images (335W, 69°C max)

  • RTX 3060 Laptop generated only 32 images (54W, 77°C max)

  • A100 80GB PCIe generated 217 images (283W, 70°C max)

These results show some interesting efficiency patterns across the different NVIDIA architectures.

Super simple to use:

pip install gpu-benchmark
gpu-benchmark

The benchmark takes about 5 minutes after initial model loading.

Would love to hear your feedback or answer any questions!

GitHub: https://github.com/yachty66/gpu-benchmark
Online benchmark results: https://www.unitedcompute.ai/gpu-benchmark

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NVIDIA
docs.nvidia.com › nvidia-hpc-benchmarks › Microbenchmarks.html
Microbenchmarks — NVIDIA HPC Benchmarks
Run NVSHMEM device put bandwidth test on NVIDIA GB200 NVL72 with affinity settings: srun -N 2 --ntasks-per-node=1 --cpu-bind=none --mpi=pmix \ ./microbenchmarks/nvshmem_device_tests.sh --op put-bw --test-params "-s 1 -e 1048576" \ --cpu-affinity 0-71 \ --mem-affinity 0 · The OSU MPI benchmarks are ...