[Benchmark] Add local OmniInteract realtime benchmark (#6522)

Signed-off-by: natureofnature <wzliu@connect.hku.hk>
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NATURE authored and GitHub committed 2026-08-25 15:32:58 +00:00
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@@ -39,4 +39,5 @@ vllm bench serve --omni \
--num-prompts 5
```
See [vllm bench serve](./bench/serve.md) for the full reference of all available arguments.
See [vllm bench serve](./bench/serve.md) for serving benchmark arguments and
dataset-specific examples, including OmniInteract native-duplex sessions.
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@@ -2,7 +2,7 @@
The vllm bench command launches the vLLM-Omni benchmark to evaluate the performance of multimodal models.
## Notes
vLLM-Omni registers the `openai-chat-omni`, `openai-audio-speech`, `openai-image-edits-omni`, and `daily-omni` serving benchmark backends.
vLLM-Omni registers the `openai-chat-omni`, `openai-audio-speech`, `openai-image-edits-omni`, `daily-omni`, and `openai-realtime-duplex` serving benchmark backends. It also adds the `omniinteract` dataset.
## Basic Parameter Description
You can use `vllm bench serve --omni --help=all` to get descriptions of all parameters. The commonly used parameters are described below:
@@ -10,7 +10,7 @@ You can use `vllm bench serve --omni --help=all` to get descriptions of all para
Enable Omni (multimodal) mode, supporting multimodal inputs and outputs such as images, videos, and audio.
- `--backend`
Specify the backend adapter. vLLM-Omni adds `openai-chat-omni`, `openai-audio-speech`, `openai-image-edits-omni`, and `daily-omni` to the upstream vLLM backend choices.
Specify the backend adapter. vLLM-Omni adds `openai-chat-omni`, `openai-audio-speech`, `openai-image-edits-omni`, `daily-omni`, and `openai-realtime-duplex` to the upstream vLLM backend choices.
- `--model`
The model identifier to load, filled according to the models supported by vLLM-Omni.
@@ -19,7 +19,7 @@ You can use `vllm bench serve --omni --help=all` to get descriptions of all para
The API endpoint exposed externally, to which clients send their requests.
- `--dataset-name`
The name of the dataset used; random-mm indicates generating random multimodal inputs (images, videos, audio).
The name of the dataset used; random-mm indicates generating random multimodal inputs (images, videos, audio), while `omniinteract` replays official OmniInteract videos.
- `--num-prompts`
The total number of requests to send, an integer.
@@ -269,6 +269,44 @@ We use audio generation time / audio duration to calculate RTF.
</details>
### OmniInteract Realtime Benchmark
OmniInteract runs each video as one native-duplex WebSocket sample in the standard serving-benchmark lifecycle:
```bash
vllm bench serve --omni \
--backend openai-realtime-duplex \
--dataset-name omniinteract \
--dataset-path /path/to/OmniInteract \
--model openbmb/MiniCPM-o-4_5 \
--base-url http://127.0.0.1:8000 \
--endpoint /v1/realtime \
--omniinteract-ref-audio /path/to/reference.wav \
--omniinteract-output-dir ./omniinteract-artifacts \
--num-prompts 3 \
--num-warmups 0
```
`--dataset-path` accepts an extracted directory, `data.tar[.gz]`, or a Hugging Face dataset ID; omitting it uses
`lucky-lance/OmniInteract`. `--num-prompts` is the total across subsets and defaults to 3 for OmniInteract; explicit `0`
selects all and oversize values use all available cases. Reference audio is required, and OmniInteract uses the
`/v1/realtime` endpoint.
Audio is replayed as 16 kHz PCM16 in 200 ms chunks and video at 1 FPS with real-time pacing. All selected media is decoded
before timing and remains in client memory for the run, so `--max-concurrency` does not limit media preparation memory; use
explicit `--num-prompts 0` only when the client has enough RAM for the full dataset. Media commands are bounded by
`--omniinteract-media-timeout-s`, and concurrency defaults to 1. Standard request-rate, warmup, result-saving, and summary
options apply. Use `--omniinteract-require-response` only for functional E2E cases; LISTEN is a valid benchmark result.
Each completed case writes `output.wav`, `wav_transcript.json`, `events.json`, `result.json`, and a final `.done` marker under
`--omniinteract-output-dir`. The root also contains `batch_summary.json` and `official_eval_manifest.jsonl`; failed cases write
`.failed.json`. Runs sharing one output root are serialized. Completion validates transport, response lifecycle, and artifacts,
not answer accuracy. Transcript timestamps are serialized playback-queue times. Clipped or cancelled outputs are ineligible and
omitted from the official manifest; `audio_clipped_bytes` records output beyond the rounded video horizon.
TTFT, TTFP, and RTF start at client receipt of `response.created`. TPOT/ITL use engine stage-0 timing; ITL is emitted only when
every token interval is present.
### Multi-Modal Benchmark
<details class="admonition abstract" markdown="1">