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If your YouTube live stream goes offline while OBS reports an out-of-memory error, first establish whether OBS actually ran out of memory. A stream going offline is an outcome, not a diagnosis: OBS may have crashed or hit an allocation error, but it may also have stayed open while its output disconnected because of network trouble, encoding load, or another problem. Match OBS logs and Stats, system and GPU memory readings, and YouTube Live Control Room messages at the same timestamp before changing settings or hardware.
First determine what failed
Write down the exact time and wording of the incident, then check what both OBS and YouTube did at that moment. “OBS runs out of memory while streaming” can describe several different failures; only some involve memory exhaustion.
- OBS process ended: Check whether OBS terminated unexpectedly and whether a crash log exists.
- OBS reported an allocation or encoder error: Record the exact message, especially any CUDA or NVENC error.
- OBS stayed open but its stream output stopped or reconnected: This points to an output interruption, but does not by itself establish a memory failure.
- YouTube reported that it was not receiving data or showed an encoder error: Record the exact Live Control Room message.
- Only some viewers reported playback trouble: Distinguish those reports from a stream that was actually offline for everyone.
Do not call an interruption a memory leak unless logs or correlated memory readings support that conclusion.
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Collect evidence before changing settings
Save the OBS session and crash logs
Keep the OBS log for the affected session and any crash log. Alongside them, note your operating system, OBS version, GPU model and driver, encoder, scene and source setup, active plugins, output resolution and frame rate, and whether recording or Replay Buffer was also running. Record whether the incident followed a stream stop, reconnect, or scene/source change.
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Watch OBS Stats at the time of the problem
In OBS versions with the applicable menu, open View → Stats. Watch Memory Usage, CPU usage, average render time, frames missed due to rendering lag, and frames skipped due to encoding lag. The separate rendering- and encoding-lag counters help distinguish graphics/rendering pressure from encoder workload; neither counter alone proves that memory caused the outage. OBS documents these interface labels in its streaming connection troubleshooting guide.
Monitor system RAM and GPU memory separately
Use your operating system or GPU vendor’s diagnostic tools to observe system RAM and GPU memory (VRAM) while streaming. Note whether memory rises steadily, spikes when a particular scene or source appears, or grows after stopping and restarting the output. Capture the precise encoder error, if any. A reading taken after OBS has recovered may miss a short-lived spike, so time-correlated observations are more useful than a single snapshot.
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Compare YouTube’s dashboard and a local recording
Check YouTube Live Control Room for encoder errors and viewer-reported errors. YouTube’s live-stream troubleshooting guidance recommends checking encoder CPU load and a local archive when stream quality is poor; when the encoder’s picture and sound look healthy, it points to testing the outbound internet connection. Compare what YouTube received with the local recording, if you have one.
Do these 3 things before closing this tab:
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Preserve the original log and setup details before testing a change, then save a new log for comparison. A short, controlled reproduction can help isolate a trigger. Avoid repeatedly restarting a live output if each restart appears to increase GPU memory use; that can add risk and muddy the evidence.
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Use the evidence to choose the next diagnostic branch
| What you observe | Likely area to investigate | Next check |
|---|---|---|
| OBS exits or explicitly reports an allocation failure, and system RAM is exhausted or OBS process memory climbs | Host RAM pressure, a source or plugin that grows in memory, or a software defect | Correlate per-process and system RAM with scenes, browser sources, plugins, and logs. A clean OBS profile can be a controlled comparison. The available sources establish no universal RAM threshold or universal source-level fix. |
CUDA/NVENC reports CUDA_ERROR_OUT_OF_MEMORY, with GPU memory rising after output stops, starts, or reconnects |
GPU VRAM or encoder allocation path | Capture GPU memory and encoder logs around each restart; compare hardware and software versions. Check the current status of the OBS issue report before deciding it applies to your setup. |
| OBS stays open, output disconnects, dropped frames rise, and no allocation failure appears | Connection to the ingest server or bitrate beyond what the connection can sustain reliably | Follow OBS’s connection checks: compare bitrate with stable upload, try another server or service where possible, review VPN, security, network-optimization software and drivers, and prefer a wired connection. |
| CPU load is high and rendering or encoding lag rises | Rendering or encoding capacity, rather than demonstrated memory exhaustion | Compare OBS Stats with YouTube encoder errors and the local archive; test a lower workload or a relevant encoder setting one change at a time. |
| Display or output initialization fails only after GPU memory has been consumed | Possible GPU resource pressure affecting more than encoding | Preserve GPU telemetry and logs. Lowering stream bitrate alone is not established as a way to restore VRAM. |
When dropped frames point to the network
OBS’s connection guide, dated September 30, 2024, frames dropped frames and intermittent disconnections as a network issue between the computer and the remote stream ingest server. It also warns that dropping too many frames can disconnect you. That guidance applies to those connection symptoms; it does not explain an explicit allocation failure.
If OBS remains open and dropped frames rise without a memory error, check the outbound path before changing RAM or GPU hardware. OBS sends to the selected streaming service’s ingest path, so the relevant connection is from your computer to that service—not a general claim that OBS has or lacks streaming servers.
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- Set the bitrate to a level your upload connection can sustain consistently, rather than relying on a brief best-case speed reading.
- Where possible, try a different ingest server or service to compare behavior.
- Check whether VPN, security, network-optimization software, or network drivers are affecting the connection.
- Prefer wired networking over Wi-Fi when practical.
- Treat dynamic bitrate as a congestion mitigation, not a root-cause repair: OBS notes that it reduces video quality.
Interpret memory-leak reports narrowly
An OBS Studio GitHub issue report from 2026 describes NVIDIA NVENC surface allocations that reportedly were not freed after output stop/start, including reconnects, eventually leading to CUDA_ERROR_OUT_OF_MEMORY. The report describes approximately 200 MiB per reconnect and a test setup with 4 GiB of VRAM. Those are measurements and conditions from that issue, not a typical rate, a general VRAM requirement, or evidence that all OBS users encounter the problem. The available issue text does not establish that every user can reproduce it or that an official fix has shipped. Check the issue’s current status rather than assuming it explains your failure.
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A separate OBS issue opened on December 7, 2023 described a leak in OBS 30.0.0-rc1 on Fedora 37 under a particular Stream Delay and RTMP-disconnect reproduction. It is an example of why leak reports need to be matched to their exact version and configuration, not proof that the same defect affects current stable OBS.
Or let it run in the cloud
If your aim is to keep uploaded videos looping on a YouTube channel, StreamNeo is a cloud alternative to leaving OBS running on a home computer. Upload a recording or build a playlist, add your YouTube stream key once, then go live. Your computer can be off; StreamNeo plays uploaded videos, not a live camera feed.
- Nothing has to stay on at home: the stream runs from the cloud.
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The monthly option is $9.99 per month. Start your free day with StreamNeo.
Quick Recap
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Quick wins for a faster PC:
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