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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsTo reduce OBS memory growth during a long-running YouTube playlist stream, first check whether the increase is system RAM or GPU memory, then test a lighter scene and add sources back one at a time. OBS says sources consume resources even when some are not visible, but rising memory use alone does not prove a leak—and the available reports do not establish one general playlist-specific fault.
What rising memory use does—and does not—tell you
OBS scenes and their sources have resource costs. The OBS Project’s Encoding Performance Troubleshooting guide says: “Every source requires some amount of resources to be shown in the scene. Most sources will also require some resources even if they are not visible.” A busy scene can therefore use more memory without having a leak.
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A leak is more plausible when memory keeps climbing over time under comparable conditions and is not released as expected. But a single high reading, or an increase around a video transition, does not establish that. The useful first question is which resource is growing and what event coincides with the increase.
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Record a baseline before changing the setup
Write down the OBS version, operating system, installed plugins, scene collection, active sources, and approximate process memory when the stream starts. If your system exposes GPU memory use, note that too. Check the same readings at regular intervals and record the times of playlist transitions, scene changes, browser activity, and stream reconnects.
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Use your operating system’s process and GPU monitoring tools, along with OBS logs available on your platform. There is no universal OBS leak detector described in the available guidance. A timeline is more useful than a lone reading: it can show whether growth tracks elapsed runtime, a particular source, or repeated output restarts.
Reduce scene and source costs
Make changes on a copy of your scene collection so you can restore the original setup. Start with sources and effects you do not need for the stream.
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- Remove unused sources and filters; temporarily disable complex animated overlays.
- Reduce the number and dimensions of browser sources. If an overlay is not essential, turn it off for a test run.
- Use an Image Source for static artwork rather than a browser page that only displays an image.
- For video or audio files, use a Media Source or VLC Source instead of a browser source when a live web page is not required.
- Where the output is smaller than the source media, test lower-resolution media. This can reduce the work associated with oversized assets; it is a diagnostic and resource-management step, not a guaranteed leak fix.
These recommendations follow the OBS Project’s guidance on source resource use. It does not provide a head-to-head benchmark for every playlist or overlay design, so compare your own scene under similar conditions rather than assuming one implementation is always lighter.
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- Run the current scene and note memory readings and event times.
- Make a minimal test scene with only what is needed to reproduce the stream, then run it for a comparable period with similar output settings.
- If growth changes, add the playlist source, overlays, filters, and plugins back one at a time. Keep the run length and settings as similar as practical.
- Record whether a change begins after a specific media transition, scene change, browser activity, or reconnect.
This is a practical isolation method, not a published OBS test protocol. One short run without visible growth cannot rule out a slow problem; compare repeated, sufficiently long runs before drawing a conclusion.
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Separate system RAM from GPU memory and reconnect symptoms
If ordinary process memory is climbing
Start with the scene comparison and source reduction above. Note whether the growth tracks a media source or scene transition. A historical report filed in 2021 described memory growth when switching scenes containing media sources in OBS 26.1.2 on macOS Big Sur 11.2.3. It is version- and environment-specific user evidence, not proof of a current general macOS problem. See OBS Studio issue #4382.
If GPU memory (VRAM) rises after reconnects with NVENC
Record whether the growth follows repeated RTMP output stop/start events. A 2026 report in OBS Studio issue #13656 describes an NVENC VRAM surface-pool leak on OBS 32.1.2 for Linux with an NVIDIA GeForce GTX 1650 SUPER, associated with periodic RTMP output reconnects. The reporter measured roughly 200 MiB per restart in that particular case and said the VRAM was reclaimed when OBS exited. This is an individual report, not confirmation that all systems, NVENC streams, or YouTube playlist streams share the issue.
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If you see dropped frames
Dropped frames are a network symptom, not a memory-leak diagnosis. The OBS Project’s Help Portal describes dropped frames as a response to an unstable or constrained connection to the streaming service. Investigate connection stability separately instead of treating dropped frames alone as evidence that RAM or VRAM is leaking.
Prepare useful evidence for support
- Save OBS logs from a run that reproduces the growth.
- Include the exact OBS version, operating system, hardware, plugins, scene and source setup, and whether the reading is process memory or VRAM.
- Note when the increase starts and whether it follows a playlist transition, scene change, or output reconnect.
The OBS Help Portal links to guides and contributor support. Specific versions and event timing make it easier to distinguish a general resource burden from a component- or configuration-specific report.
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Cost and upgrade considerations
Buying more RAM may increase available capacity, but it does not establish or repair a software leak. Begin with system monitoring, OBS logs, and controlled source isolation; the supported troubleshooting steps above do not require a hardware purchase.
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