Start by simplifying OBS, not by assuming the playlist is leaking memory. OBS says sources consume resources even when they are not visible, so remove or disable what the stream does not need, then track system RAM and GPU memory separately while testing. A long playlist is context, not a diagnosis: the cause depends on your sources, scene design, OBS version, operating system, and encoder path.
Reduce memory use with reversible OBS changes
Make one change at a time and note the memory reading before and after. Save a copy of your scene collection first so you can restore it if a change affects the stream.
Remove sources the stream does not need
In OBS, review each scene and its Sources list. Hide or remove unused captures, overlays, browser sources, and media sources. A hidden source may still consume resources; OBS’s Encoding Performance Troubleshooting guide says, “Most sources will also require some resources even if they are not visible.” Complex scenes and large scene collections can also require more resources.
Simplify browser sources and overlays
Reduce the number and dimensions of browser sources where practical. Temporarily disable overlays that rely on complex JavaScript and compare memory use. This is a diagnostic step: if memory changes substantially, investigate that overlay or source rather than assuming the playlist itself is responsible.
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Use appropriately sized media
Match media dimensions to the stream output where possible. OBS cautions against unnecessarily large media—for example, 4K media when the stream is not 4K—and notes that full-canvas media or browser sources with large empty areas still use resources. For a static image, use an image source rather than a larger or more complex source type. OBS suggests Media Source or VLC Source for video and audio files.
Do not switch a playlist from a browser to local media simply as a blanket fix: use the source type that matches how your playlist actually reaches OBS.
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Trim filters and effects
Disable filters the stream does not need. If a filter is necessary, apply it to the smallest practical source rather than a full-canvas source when the effect does not need to cover the whole canvas.
Compare a minimal scene with the full stream
- Record your OBS version, operating system, source types, and system RAM and GPU memory readings at the start of the stream.
- Create or switch to a stripped-down test scene with only the source needed to reproduce the playlist stream.
- Observe the same memory readings over time under comparable streaming conditions.
- Add sources back one by one, checking readings after each addition. If growth follows one source, test or replace that source before changing unrelated settings.
This isolation procedure follows from OBS’s guidance that sources have resource costs; it is a diagnostic method, not a published benchmark.
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Tell system RAM and GPU memory apart
System RAM and GPU video memory (VRAM) are different resources. Record both separately, along with the operating system, OBS version, source types, and when any growth occurs. If system RAM rises with a particular scene element, isolate sources and filters. If system RAM stays stable but VRAM rises around output stop-and-restart events, investigate the GPU encoder path and OBS logs rather than treating it as ordinary RAM pressure.
One specific OBS GitHub issue reports NVENC VRAM allocations accumulating after repeated output stop/start in a setup using OBS 32.1.2 on Linux, an NVIDIA GTX 1650 SUPER, and a particular NVENC configuration: the report is setup-specific. It is not evidence that YouTube playlists generally cause a memory leak or that other versions and platforms are affected.
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What reported memory figures do—and do not—show
No current authoritative benchmark establishes expected OBS memory use during a long YouTube playlist stream. A March 2021 individual report described presumed media-source memory growth in OBS 26.1.2 on macOS Big Sur 11.2.3: the reporter said a minimal project used 3 GB on a system with 64 GB of RAM. Those figures describe that person’s historical setup, not typical use or a current-version benchmark. See the historical issue report.
OBS Studio 27.2.1 release notes recorded a fix for a PipeWire-capture memory leak on Linux and an improvement to browser-source performance. These are version-specific historical changes, not a diagnosis of a present-day playlist stream; see the OBS release notes.
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When to consider a hardware change
More RAM does not generally reduce OBS’s memory use or repair a leak. Consider a compatible capacity upgrade only if measurements show sustained, system-wide pressure—for example, the computer is short of physical memory while running the stream and other necessary applications. Check the computer or motherboard’s memory compatibility before buying. Without the model and configuration of your device, a specific RAM module cannot be recommended.
Troubleshoot the symptom you observe
- Memory climbs when a particular overlay or source is enabled: disable it, reduce its dimensions, or test a simpler replacement; then add it back to confirm whether the change tracks that source.
- Memory is high even with sources hidden: remove sources the stream does not need. OBS notes that invisible sources may still use resources.
- VRAM rises around output reconnects while system RAM is steady: record the OBS version, GPU, operating system, encoder, and restart sequence, then inspect OBS logs and investigate the relevant encoder or driver path.
- The result differs between a minimal scene and the full scene: add scene elements back individually to identify which source, browser overlay, or filter changes the reading.
- The whole computer runs short of physical memory: close unnecessary applications and check whether the measured pressure persists. Only then assess a device-compatible RAM upgrade; it is a capacity measure, not a demonstrated fix for a leak.
Or let it run in the cloud
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