A long YouTube playlist does not, by itself, explain rising OBS memory use. Start by measuring whether system RAM or GPU memory is increasing, then simplify sources and test changes one at a time before considering hardware.
OBS uses resources for sources in a scene, including some that are not visible. A playlist may simply be the setting in which a source, filter, overlay, or output-path problem becomes noticeable; without your OBS version, operating system, and readings, the cause remains uncertain.
Measure memory across the stream
Take a reading shortly after OBS and the stream are running, then record later readings during the same session. Use your operating system’s process monitor to note OBS’s system RAM use, and, where available, its GPU memory use separately. Also note the time, whether the stream briefly disconnected or the output was restarted, and what was playing. A single reading cannot show whether memory is steadily growing, settling at a higher level, or fluctuating as expected when sources load.
Keep the test conditions as consistent as you can. Record the OBS version, operating system, scene collection, source types, output resolution and whether you changed scenes. If you alter several things between readings, you may reduce the total load without learning which change mattered. A short written log is sufficient: “start”, “later”, “source disabled”, and the corresponding readings.
System RAM and GPU VRAM are different pools. If OBS’s system RAM rises, investigate source and filter use first. If system RAM remains fairly steady but VRAM rises, note whether that coincides with encoder activity or repeated output stop-and-start cycles; that pattern calls for a different investigation. Check OBS’s current guidance and logs rather than assuming a playlist itself is responsible. The OBS performance troubleshooting guide explains how sources contribute to resource use, but it does not provide a normal memory target for every scene and machine.
There is no reliable universal “correct” OBS memory figure for a long playlist. A project with several video sources, browser overlays and filters is not comparable to a single media source on the same computer. Focus on whether memory keeps climbing under stable conditions, whether the whole machine is under pressure, and what changes when you simplify the scene.
Inspect scenes and scene collections
Open the scene collection you actually use for the stream and examine each scene, not just the one currently on screen. OBS notes that complex scenes and large collections can require more resources. A scene collection built for production work may contain alternate layouts, cameras, graphics or test sources that are not needed for an unattended playlist.
Before removing anything permanently, make a copy of the collection or save a backup. Then create a stripped-down test scene with only what the broadcast needs, such as the playlist source and a simple static logo if required. Keep the stream’s output settings unchanged while comparing it with your working scene. If memory behaves differently in the stripped-down version, add the other elements back gradually.
This is a reversible diagnostic, not a promise that fewer scenes always solve a problem. Scene count alone may not be the cause; a single animated or browser-based source can matter more than several simple image sources. If you are arranging a channel around a recorded playlist, the guide to running a 24/7 YouTube gaming stream from a playlist offers relevant workflow context, while the memory test here is about what OBS is actually loading.
Keep a distinction between simplifying what OBS must render and changing how the playlist is delivered. Do not switch a browser-based workflow to local media solely on the assumption that playlists leak memory. First identify the source type in your own scene and test that source in isolation.
Remove or disable sources you do not need
In each scene, review the Sources list and identify elements that are no longer part of the broadcast: an old webcam, a second logo, a test capture, a spare alert or an unused audio visualiser. Disable or remove one at a time, then watch both the picture and sound to ensure you have not removed something needed. This is easier to reverse when you have a saved copy of the collection.
For media, match the file to the actual stream output. OBS advises against unnecessarily large media, for example using 4K video when the stream is not 4K. A source that fills the canvas but contains large unused margins may also do work that contributes nothing visible. If you have an oversized asset, test a copy scaled to the intended output dimensions rather than replacing the only original.
Filters deserve the same review. Disable filters you do not need, one at a time. If an effect is needed, test whether it can be applied to a smaller source rather than a full-canvas layer. Keep track of the change and check that the output still looks and sounds right; a lower memory reading is not useful if the stream loses an essential label or audio treatment.
For simple static artwork, OBS recommends an image source. For video or audio files, its guide points to Media Source or VLC Source as relevant source types. That is not a reason to convert every playlist to local files: use the source that fits your existing workflow, then measure its impact. If a file fails to load or behave as expected, troubleshoot that separately with the OBS file-opening guide.
Check sources that are hidden
A hidden source is not necessarily an inactive source. OBS’s Encoding Performance Troubleshooting guide says that most sources still require some resources even when they are not visible. That makes hidden items a practical place to look when a scene appears simple but OBS continues to use memory.
Expand the source list and inspect items with visibility turned off, including nested sources and elements inside groups. Ask whether each one is needed during this broadcast. A source can be hidden because it is meant for a different scene, retained for a future layout, or accidentally left behind after an experiment. Disable or remove unneeded items, then test again rather than relying on the eye icon as proof that the source costs nothing.
Be careful with elements that seem redundant but carry audio, transitions or scene-specific content. A hidden audio source may still be part of the intended mix, and a nested source may be shared by another scene. Check the relevant scenes and listen to the stream output before deleting shared elements. If you cannot tell what a source does, rename it or test a copy of the collection rather than making a blind change during a live broadcast.
Reduce browser-source count and dimensions
Browser sources can host useful overlays, dashboards and dynamic graphics, but each adds another thing for OBS to manage. Count them across the scenes you use and look for duplicates, including a browser overlay repeated in several scenes when one shared source would meet the same need. Change one item at a time so you can see whether the count or a particular source is associated with the rise.
Set the browser source to dimensions suited to the overlay, not automatically to the full stream canvas. A small clock or label does not need a full-screen browser area. OBS also cautions that browser sources with empty space can consume resources despite little visible content. Crop or resize thoughtfully, then preview the scene and check that the layout remains correct at the intended output size.
If an overlay runs complex JavaScript, temporarily disable it and observe memory over a comparable period. Do not infer that every browser source is a problem: a plain, modest overlay may be important to your channel, and its cost depends on what it does. If disabling one particular overlay changes the pattern, investigate its content or ask its provider for guidance before rebuilding the whole scene.
For a static logo or background, test an image source instead of keeping a browser open just to display an unchanging graphic. For motion, retain the appropriate media source rather than replacing it with an unrelated format. A devotional channel with a static title card and a moving playlist, for instance, may be able to simplify a browser-based title graphic without changing how the playlist itself enters OBS.
Test complex overlays on their own
When an overlay is suspected, isolate it rather than stripping every scene element at once. Save a copy of the scene collection, disable the overlay, and run the same stream conditions for a comparable observation window. If memory no longer climbs in the same way, re-enable it and repeat once to check whether the pattern follows that change. This is a practical inference from OBS’s documented per-source resource costs, not a controlled benchmark.
Try likely complexity reductions individually: pause an animated element, remove a rotating background, reduce the browser dimensions, or turn off a filter tied to the overlay. Keep notes about each test. An overlay can involve several layers, so changing everything at once may point you to the general scene but not the specific source worth replacing.
Do not leave a needed alert, donation message or channel label disabled just because a short test looks better. Confirm the broadcast still meets your operational needs, and consider whether the overlay is essential during the full playlist or only during occasional announcements. If you need a minimal always-on layout, the cloud playout overview can help frame the broader choice between running a local OBS scene and using a different way to keep recorded content on air.
Compare after each change
Use a small comparison table or log so your next decision rests on evidence rather than memory. Keep the same stream output and observe comparable intervals; avoid changing the playlist, scene, resolution and encoder all in the same test. Record the system RAM and VRAM readings separately where you can.
| Test | Change made | What to record | What it can suggest |
|---|---|---|---|
| Baseline | No change | OBS version, scene, RAM and VRAM over time | Establishes the pattern to compare |
| Simplified scene | Use only required sources | Same readings and visible/audio checks | Whether overall scene complexity matters |
| Hidden sources | Disable one unused source | Readings before and after | Whether an invisible item contributes |
| Browser overlay | Disable or resize one overlay | Readings and overlay behaviour | Whether that source deserves closer review |
| Reconnection pattern | Note output stop/start events | VRAM and logs around the event | Whether the encoder path merits investigation |
If memory falls after a change, keep that configuration for a longer real-world check before treating the matter as settled. If it rises again, add back only the sources you need and repeat the comparison. If none of the reversible tests changes the pattern, preserve the notes and logs; they will make a version-specific support question more useful.
A GitHub issue can show that a particular setup has been reported, but it cannot establish the cause on your machine. One issue describes accumulating NVENC VRAM allocations after repeated output stop/start in a specific Linux and NVIDIA configuration, using OBS 32.1.2; it is not evidence that YouTube playlists generally cause memory leaks. Review the report’s exact details at the OBS Studio issue page and compare them with your platform and event pattern before drawing a parallel.
Another issue records an individual report about media-source memory growth in OBS 26.1.2 on macOS Big Sur. That historical report is likewise not a current benchmark or a typical memory figure. OBS release notes have also documented specific fixes in particular releases, including browser-source performance and a PipeWire-capture leak; version-specific notes are reasons to check your version and platform, not to presume the same defect applies. See the OBS Studio release notes and check current official guidance for your case.
If the evidence shows sustained system-wide memory pressure, first close unrelated applications and confirm which processes are using memory. Consider a compatible capacity upgrade only if measurement shows the computer is short of physical RAM and you have confirmed the device supports it. More RAM does not reduce OBS’s source use or repair a leak, and it will not directly address GPU VRAM growth. Do not buy hardware before the reversible scene tests and diagnosis.
If running OBS itself through a long unattended session is the recurring operational burden, StreamNeo removes the need to keep that local OBS computer running by taking an uploaded video and stream key to a 24/7 YouTube broadcast. It is YouTube-only, so it is not a fix for a specific OBS project you still need to run locally.
Before committing, compare the operating options on the pricing page. When the file and channel are ready, start free — 24-hour trial, no card.
FAQ
Does a YouTube playlist make OBS memory leak?
A playlist alone does not establish a memory leak. Measure RAM and VRAM, then test the sources, filters and scenes that run alongside it. A leak is a diagnosis to support with evidence, not a label for any increase over time.
Should I upgrade RAM if OBS memory keeps rising?
Not as the first step. Simplify the scene and identify whether system RAM or GPU VRAM is rising; consider compatible RAM only when measurements show sustained system-wide physical-memory pressure. A capacity upgrade does not reduce source costs or resolve every growth pattern.
Do hidden OBS sources use memory?
Some sources can use resources while not visible, according to OBS’s performance guide. Inspect hidden and nested sources, but check shared scenes and audio before removing anything. Test changes on a saved copy where possible.
What if GPU memory rises after reconnecting the stream?
Record the event and check logs, OBS version, operating system and encoder details. A specific report of VRAM accumulation after repeated output restarts exists for one setup, but it does not prove the same cause in yours. Compare your case with current official guidance or seek support with those details.