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If OBS memory usage keeps climbing during a long YouTube stream, first find out whether the growth is in system RAM or GPU VRAM and what triggers it. A rising graph alone does not prove OBS has a memory leak. Use controlled tests to separate source or scene workload, output stop-and-start behavior, rendering or encoding strain, and network trouble.
First identify what is growing
System RAM and GPU VRAM are different resources, so note which one rises rather than treating “memory” as a single measure. Also record whether usage falls when OBS is idle, when a source is hidden, or when stream output stops. These observations help narrow the cause; none alone confirms a leak.
- System RAM: memory used by OBS and other running applications.
- GPU VRAM: graphics memory used by the GPU. An OBS Studio issue report describes a specific NVENC VRAM-retention symptom after output stop/start cycles, but it does not establish a general cause for other users. Check the issue report and its current status.
Track the symptom alongside its context: elapsed time, active output, scene or source changes, reconnects, and whether the observed change is steady or occurs in jumps.
Record a baseline and reproduce the trigger
Before changing settings, write down your OBS version, operating system, GPU and driver, encoder, active plugins, scene collection, and whether RAM or VRAM is increasing. Take timestamped observations at startup and at regular intervals. Reproduce the long session or reconnect pattern that causes the problem; a brief test may not reveal it.
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Compare OBS with the same scenes open but no stream output against a run with output active. If growth appears only after repeated output stops and restarts or reconnects, that is useful evidence to investigate alongside the NVENC issue report—not proof that the report describes your case.
Isolate scene and source workload
Change one category at a time and run long enough to include the original trigger. Otherwise, you cannot tell which change affected the memory trend.
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- Temporarily disable browser sources, particularly animated overlays or pages, and compare the trend.
- Test heavy filters and unused sources or scenes separately. Keep the scene collection focused while testing.
- Where a browser source is necessary, reduce its dimensions. Consider a static image or media source instead when that suits the content.
- After each change, repeat a comparable long run. Restore a setting if removing it makes no reproducible difference.
OBS’s Encoding Performance Troubleshooting guide, dated 2021-06-12, identifies GPU workload, complex scenes, browser sources, and filters as performance considerations. Its recommendations can guide workload isolation; they do not diagnose a particular memory increase as a leak.
Separate memory growth from lag and connection problems
Rendering or encoding lag
Note rendering lag and encoding lag separately from RAM or VRAM. OBS explains that GPU load and scene complexity can constrain rendering and encoding. Lag may therefore point to workload pressure even when memory is not steadily increasing; it is not, by itself, a memory-leak diagnosis. Keep the OBS Stats dock and log context available during your test.
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Dropped frames or disconnections
Dropped frames and intermittent disconnections are network or ingest symptoms, not proof of a memory leak. If those are the main issue, follow OBS’s Stream Connection Troubleshooting guide, dated 2024-09-30, and investigate connection and ingest stability separately from memory usage.
What to do if the growth persists
Repeat runs after each controlled change, keeping the trigger and observation period comparable. If memory still rises with a minimal scene and without the relevant source or plugin, preserve your logs and document reproducible steps. Share them with OBS support or the maintainer of the relevant plugin or driver, as appropriate. Do not assume a hardware upgrade or cleanup utility will fix the issue without evidence identifying a hardware constraint.
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