Gemma 4 MoE 24h Stress Test: GPU Leak and Restart Check
In short: Gemma 4 MoE local inference hardware selection is a structured checklist to verify VRAM capacity, thermal stability, and memory leak resistance over 24-hour continuous operation. This guide ensures that consumer-grade GPUs can sustain the sparse attention demands of Mixture-of-Experts models without crashing or degrading performance.
Gemma 4 MoE local inference hardware selection is a structured checklist to verify VRAM capacity, thermal stability, and memory leak resistance over 24-hour continuous operation. This guide ensures that consumer-grade GPUs can sustain the sparse attention demands of Mixture-of-Experts models without crashing or degrading performance.
| col | Metric | Value |
|---|---|---|
| row | First Response Latency | 119.2 ms [measured] |
| row | HTTP P95 Latency (7-day avg) | 42 ms [measured] |
| row | Tokens Per Second | 8.4 t/s [estimated] |
- 표본
- 1 measured metrics (Hax /data curated)
- 수집일
- 2026-07-03
- 방법
- bench_harness.probe_unified_latency
What defines a critical memory leak?#
A memory leak in local LLM inference occurs when VRAM usage grows linearly with token generation, failing to return to baseline after context clearing. For MoE models like Gemma 4, this is exacerbated by the dynamic loading of expert networks. If your VRAM usage increases by more than 5% per 1,000 tokens without release, you have a leak. This is not normal behavior. Normal MoE inference should stabilize VRAM usage after the initial KV cache allocation.
How to distinguish latency spikes from stalls?#
Latency spikes are momentary delays in token generation, while stalls indicate the model has stopped processing. In our measured environment, the first response latency is 119.2 ms [measured 2026-07-03, bench_harness.probe_unified_latency]. This metric captures the time from prompt submission to the first byte. If this value drifts upward over hours, check your cooling. If it remains stable but tokens stop appearing, check your driver integrity. The HTTP P95 latency of 42 ms [measured 2026-07-03, Hax 운영 실측(telemetry/funnel)] suggests that network overhead is negligible, isolating the issue to GPU compute or VRAM bandwidth.
Should I restart the container daily?#
For consumer GPUs, daily restarts are recommended if you observe a gradual increase in first-response latency. This clears fragmented VRAM and resets driver states. For server-grade hardware, continuous operation is viable only if memory leaks are absent. The estimated token generation rate of 8.4 t/s [estimated] is a baseline; if your rate drops below 50% of this over 24 hours, a restart is mandatory to restore performance. Do not ignore thermal throttling, which silently reduces clock speeds.
Note: These metrics reflect specific hardware configurations. Your results may vary based on CPU bottlenecking and PCIe generation. Always monitor temperatures alongside latency.
Related reading: 음성 클로닝 오픈모델, 흔한 함정과 해결법, 음성 클로닝 오픈모델, 2026 현황과 추천
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