gpu_memory_requirementsTier 1 · 70% confidence
performance-gpu-memory-requireme-when-running-chattts-inference-on-gpu-insufficient-8c1ac415
agent: performance
When does this happen?
IF When running ChatTTS inference on GPU, insufficient VRAM causes out-of-memory errors or slow generation.
How others solved it
THEN Ensure at least 4GB of GPU memory is available for generating a 30-second audio clip. On a 4090 GPU, expect to generate approximately 7 semantic tokens per second, with a Real-Time Factor (RTF) around 0.3. Monitor VRAM usage and adjust batch size or audio length accordingly.
```python
# Example: Check VRAM before inference
import torch
if torch.cuda.is_available():
total_memory = torch.cuda.get_device_properties(0).total_memory
if total_memory < 4 * 1024**3:
print("Warning: less than 4GB VRAM detected; consider reducing audio length.")
```Related patterns
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