This page is for AIPerf, version v0.8.0.
For other versions, use one of these documentation indexes:
- Latest (v0.13.0) (default): https://docs.nvidia.com/aiperf/latest/llms.txt
- dev: https://docs.nvidia.com/aiperf/dev/llms.txt
- v0.13.0: https://docs.nvidia.com/aiperf/v0.13.0/llms.txt
- v0.12.0: https://docs.nvidia.com/aiperf/v0.12.0/llms.txt
- v0.11.0: https://docs.nvidia.com/aiperf/v0.11.0/llms.txt
- v0.9.0: https://docs.nvidia.com/aiperf/v0.9.0/llms.txt
- v0.8.0: https://docs.nvidia.com/aiperf/v0.8.0/llms.txt
- v0.7.0: https://docs.nvidia.com/aiperf/v0.7.0/llms.txt
This document describes datasets that AIPerf can use to generate stimulus. Additional support is under development, so check back often.
Dataset Options
| Dataset | Support | Data Source |
|---|---|---|
| Synthetic Text | ✅ | Synthetically generated text prompts pulled from Shakespeare |
| Synthetic Audio | ✅ | Synthetically generated audio samples |
| Synthetic Images | ✅ | Synthetically generated image samples |
| Custom Data | ✅ | —input-file your_file.jsonl —custom-dataset-type single_turn |
| Mooncake | ✅ | Mooncake trace file —input-file your_trace_file.jsonl —custom-dataset-type mooncake_trace |
| ShareGPT | ✅ | Conversations from —public-dataset sharegpt |
| Agentic Code | ✅ | Synthetic multi-turn coding-agent traces with shared prompt layers, repository context, and cache-aware turn growth. Generated via aiperf synthesize agentic-code and replayed as a Mooncake trace. |