StreamEval
Streaming video generation models handle 300 scripted cases of 15 to 300 seconds. Requests arrive over time across avatar dialogue, performance, world generation and editing.
85 HF paper upvotes and about 610 GitHub stars two weeks after release.
In the authors’ words
We introduce StreamEval with four key features: (1) First interactive streaming video generation benchmark. (2) Fully open source. Benchmark data, evaluation code, protocols, and scoring rules are publicly available. (3) Comprehensive coverage. Five tasks cover avatar dialogue, avatar performance, world generation, instruction editing, and reference editing, with 300 scripted cases lasting 15 to 300 seconds. Ten metrics assess task execution, state consistency, visual fidelity, and audiovisual coordination. (4) Monthly updates. We will evaluate new and updated models and publish leaderboard results monthly. Results from 37 models show that high visual quality and identity retention do not necessarily coincide with reliable request execution or sustained state consistency. The leaderboard is available at https://streameval.ai.
- Level
- Everyday Most adults, without training
- Scored
- Graded by a model A language model scores each response, usually against a rubric.
- Answers
- Open-ended Free-form text, documents, designs or media judged as a whole.
No scores here yet
We have no scores for StreamEval yet.
No lab model card reports it yet
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.
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