Monitor GPU Memory Usage During FFmpeg NVENC Transcode

Monitoring GPU memory (VRAM) usage during an FFmpeg NVENC transcode is essential for optimizing stream density, preventing out-of-memory errors, and ensuring hardware stability. This guide provides practical methods to track VRAM allocation in real time using native NVIDIA utilities, dedicated terminal monitoring tools, and automated logging commands.

Using NVIDIA System Management Interface (nvidia-smi)

The standard and most reliable method to inspect NVIDIA VRAM usage is the nvidia-smi command-line tool, which is included automatically with NVIDIA display drivers.

1. Real-Time Terminal Refresh

To continuously monitor memory and encoder load every second, use the loop flag:

nvidia-smi -l 1

This updates the console every second, displaying total memory usage, temperature, power draw, and a list of active processes consuming VRAM at the bottom.

2. Querying Memory Metrics Specifically

To isolate VRAM numbers and avoid parsing the full interface, query specific memory metrics:

nvidia-smi --query-gpu=timestamp,memory.used,memory.free,memory.total,utilization.memory,utilization.gpu --format=csv -l 1
  • memory.used: Current VRAM allocated.
  • memory.free: Remaining VRAM available for additional transcodes.
  • memory.total: Total physical VRAM on the card.
  • utilization.memory: Percentage of time memory was read or written to.

3. Monitoring the FFmpeg Process Directly

If multiple workloads run on the same GPU, you can monitor the exact memory assigned specifically to the FFmpeg process:

nvidia-smi --query-compute-apps=pid,process_name,used_memory --format=csv -l 1

Using NVTOP for an Interactive UI

nvtop is a terminal-based monitoring tool designed for GPUs, functioning similarly to htop. It visually maps memory consumption, GPU load, and per-process allocations over time.

Installation

  • Ubuntu/Debian: sudo apt install nvtop
  • Fedora/RHEL: sudo dnf install nvtop
  • Arch Linux: sudo pacman -S nvtop

Usage

Run the command directly while your transcode is running:

nvtop

In the interface, locate the ffmpeg entry under the process list. The GPU MEM% and GPU MEM columns show real-time dedicated VRAM usage.

Logging Memory Usage to a File

If you are benchmarking FFmpeg transcode presets and need to record memory spikes over the entire duration of a job, pipe the metrics to a CSV file:

nvidia-smi --query-gpu=timestamp,memory.used --format=csv,noheader,nounits -l 1 > nvenc_memory_log.csv

Run this command in the background while FFmpeg executes to capture second-by-second memory profiles for post-transcode analysis.