---
format: "aidr-story-markdown/v1"
id: "36f5a9f6ff0521d9aacd1a2bb3ff1cff665a0be72c4efe173e063ee6858880b9"
canonical_url: "https://aidr.today/36f5a9f6?lang=en"
title: "StreamEval: Evaluating Interactive Streaming Video Generation Models"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
translation_fallback: null
fallback_fields: []
published_at: "2026-10-22T00:00:00.000Z"
category: "Research"
topics: ["inference"]
source_urls: ["https://huggingface.co/papers/2610.28402"]
summary: "StreamEval, a new benchmark for interactive streaming video generation, evaluates models across five tasks using 300 test cases and four dimensions, finding that high visual quality does not necessarily align with reliable request execution or state consistency."
---

# StreamEval: Evaluating Interactive Streaming Video Generation Models

> [Open the canonical story](<https://aidr.today/36f5a9f6?lang=en>)

**Published:** 2026-10-22T00:00:00.000Z
**Category:** Research
**Topics:** inference

## Summary

StreamEval, a new benchmark for interactive streaming video generation, evaluates models across five tasks using 300 test cases and four dimensions, finding that high visual quality does not necessarily align with reliable request execution or state consistency\.

## Sources

- [Story source](<https://huggingface.co/papers/2610.28402>)