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If OBS memory keeps climbing during a long YouTube playlist stream, first determine whether the increase is ordinary resource use, system RAM growth, or GPU VRAM growth. Then lighten the scene and test components one at a time. There is no general, established OBS fault specific to YouTube playlists; the cause depends on the sources, plugins, encoder, operating system, and what happens when memory rises.
First, confirm what is growing
More memory use over time does not by itself prove a leak. OBS sources consume resources to appear in a scene, and some continue to use resources even while hidden. A browser overlay, large media file, filter, or plugin can add load without the playlist itself being defective. OBS’s Encoding Performance Troubleshooting guide explains the ongoing resource cost of sources.
- System RAM: Watch OBS’s process memory in your operating system’s process monitor.
- GPU memory (VRAM): Check GPU memory separately if the machine has a discrete GPU and the reported increase appears there.
- Network symptoms: Dropped frames are not a memory-leak diagnosis. OBS describes them as a response to an unstable or constrained connection to the streaming service in its Help Portal.
Establish a useful baseline
Before changing settings, note the OBS version, operating system, plugins, scene collection, active sources, and starting RAM and—if relevant—VRAM. Check the same readings at regular intervals during a reproduction. Record when the increase begins and whether it follows a playlist transition, scene switch, browser activity, or stream reconnect. Use your platform’s process and GPU monitoring; there is no universal OBS leak detector established by the sources here.
Save the OBS log from the reproduction and write down the relevant times and actions. That makes a report more useful than a memory reading alone.
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Reduce the scene’s ongoing resource load
Make changes in a copy of your scene collection so you can restore the original setup. OBS’s resource guidance supports reducing sources, media, filters, and browser-source overhead.
- Remove unused sources and filters, including sources that are hidden but no longer needed.
- Use media at a resolution appropriate to the stream output instead of unnecessarily oversized files.
- Reduce the number and dimensions of browser sources. Temporarily disable complex or animated overlays to see whether the memory pattern changes.
- Use an Image Source for static artwork rather than a browser page. For video or audio files, use a Media Source or VLC Source where appropriate.
- Keep the scene collection focused on the sources needed for the playlist stream.
Isolate the trigger with controlled comparisons
Keep stream duration and output settings similar across comparisons; one short run cannot rule out a slow leak. Change one category at a time and track RAM and VRAM separately.
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- Run a minimal scene for a comparable period and record the readings.
- Add the playlist or media source and repeat the observation.
- Add overlays, filters, and plugins back one at a time, keeping notes on when growth changes.
- Compare the timing with scene switches, media transitions, and output reconnects. If the increase follows one of these events, reproduce that event deliberately and document it.
This is a practical troubleshooting method, not a published OBS test protocol or a benchmark of playlist implementations. It helps distinguish a source or event correlated with growth from the assumption that YouTube playlist playback is responsible.
Check for a reconnect-related VRAM pattern
A specific OBS Studio GitHub report describes an NVENC VRAM surface-pool issue on Linux with OBS 32.1.2, an NVIDIA GeForce GTX 1650 SUPER, and periodic RTMP output reconnects. The reporter associated accumulation with encoder output stopping and restarting, and reported roughly 200 MiB per restart in that configuration; the report says the VRAM was reclaimed when OBS exited. See issue #13656. This is an individual issue report, not confirmation that every OBS installation is affected or that a YouTube playlist causes it. If your VRAM increase follows repeated reconnects while using NVENC, note that sequence and compare your versions and hardware with the report.
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Account for older, version-specific reports
A separate 2021 report described memory growth while switching between scenes containing media sources on macOS Big Sur 11.2.3 with OBS 26.1.2. It is historical, version-specific user evidence, not proof of a current macOS problem. Its practical lesson is to record the OBS version and correlate growth with scene changes rather than assume all media sources or systems behave alike. See issue #4382.
When to report the problem
If a lean scene and controlled comparisons still show sustained growth, preserve the reproduction log and report the exact environment and sequence. Include OBS version, operating system, hardware, plugins, whether the growth is RAM or VRAM, when it starts, and whether it follows a scene change, media transition, or reconnect. The OBS Help Portal provides routes to help and contributor support.
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