Video Transcoding Benchmark

A simple CLI tool to benchmark video transcoding performance on your system. Measures how many simultaneous 1080p video streams can be transcoded in real-time or better.

Features

• Hardware Acceleration Support: Automatically detects and uses available hardware acceleration:

  • NVIDIA NVENC (CUDA)
  • Intel Quick Sync Video (QSV)
  • AMD AMF/VCE
  • Apple VideoToolbox (macOS/iOS ARM)
  • VA-API (Linux Intel/AMD)
  • Falls back to software encoding (libx264) if no hardware acceleration available

• Cross-Platform: Works on Linux, macOS, and Windows

• Cross-Architecture: Supports both Intel/AMD x86_64 and ARM architectures

• Simple Output: Produces a single number representing transcoding capacity

Requirements

• Python 3.6+
• FFmpeg (with hardware acceleration support compiled in if desired)

Installation

1. Install FFmpeg

Ubuntu/Debian

sudo apt update
sudo apt install ffmpeg

For hardware acceleration support:

# Intel QSV
sudo apt install intel-media-va-driver-non-free

# NVIDIA NVENC (requires NVIDIA drivers)
# Already supported if NVIDIA drivers are installed

# AMD VA-API
sudo apt install mesa-va-drivers

macOS

brew install ffmpeg

Windows

Download from ffmpeg.org or use:

choco install ffmpeg

2. Make the script executable (Linux/macOS)

chmod +x transcode_bench.py

Usage

Basic Usage

python3 transcode_bench.py

This will:

1. Detect available hardware acceleration
2. Generate a 30-second 1080p test video
3. Run benchmarks to find the maximum number of simultaneous streams
4. Output the result

Command-Line Options

python3 transcode_bench.py [OPTIONS]

Options:
  --duration SECONDS    Test video duration (default: 30)
  --input FILE          Use existing video file instead of generating one
  --min-fps FPS         Minimum FPS to consider real-time (default: 30.0)
  --help                Show help message

Examples

Use a shorter test video (faster benchmark):

python3 transcode_bench.py --duration 10

Use your own video file:

python3 transcode_bench.py --input /path/to/your/video.mp4

Set a different real-time threshold (e.g., 60fps):

python3 transcode_bench.py --min-fps 60

Output

The benchmark will display progress as it searches for the maximum number of streams, then output a final score:

==============================================================
Video Transcoding Benchmark
==============================================================
Detected acceleration: NVIDIA NVENC
Encoder: h264_nvenc
Generating 30s 1080p test video...

Benchmarking with NVIDIA NVENC...
Finding maximum simultaneous 1080p streams at real-time or better...

Testing 32 simultaneous streams...  (avg 87.3 fps)
Testing 48 simultaneous streams...  (avg 58.2 fps)
Testing 56 simultaneous streams...  (avg 24.1 fps - below real-time)
Testing 52 simultaneous streams...  (avg 45.7 fps)
Testing 54 simultaneous streams...  (avg 32.8 fps)
Testing 55 simultaneous streams...  (avg 28.9 fps - below real-time)

==============================================================
BENCHMARK RESULTS
==============================================================
Hardware Acceleration: NVIDIA NVENC
Maximum Simultaneous 1080p Streams: 54
(at 30.0 FPS or better)
==============================================================

Benchmark Score: 54

How It Works

1. Detection: Scans for available hardware encoders in your FFmpeg build
2. Test Video: Generates a synthetic 1080p video with test patterns
3. Binary Search: Uses binary search to efficiently find the maximum number of streams that can be transcoded simultaneously while maintaining real-time performance (e30 FPS)
4. Parallel Execution: Runs multiple FFmpeg processes in parallel to simulate concurrent transcoding workloads

Interpreting Results

The "Benchmark Score" represents how many 1080p video streams your system can transcode simultaneously while maintaining real-time or better performance. This is useful for:

• Comparing hardware performance
• Capacity planning for video processing workloads
• Evaluating hardware acceleration effectiveness

Typical scores:

• Software (CPU only): 1-4 streams
• Entry-level GPU: 5-15 streams
• Mid-range GPU: 15-40 streams
• High-end GPU: 40-100+ streams

Troubleshooting

FFmpeg not found:

• Ensure FFmpeg is installed and in your system PATH
• Try running ffmpeg -version to verify

Hardware acceleration not detected:

• Verify your FFmpeg build includes hardware encoder support: ffmpeg -encoders | grep <encoder>
• Ensure proper drivers are installed (NVIDIA, Intel, AMD)
• On Linux, check that you have access to /dev/dri/renderD128 for VA-API

Benchmark fails or hangs:

• Try a shorter duration: --duration 10
• Check system resources (CPU, memory, GPU)
• Verify FFmpeg works manually: ffmpeg -i input.mp4 -c:v h264_nvenc output.mp4

License

MIT License