# What it measures (R1): an Elo-like composite on OpenArt's own Arena, anchored at MiniMax H3 = 1,000; weights 30% general capabilities, 17.5% talking, 17.5% singing, 17.5% multi-character speaker assignment, 17.5% multilingual. Outputs are generated by OpenArt from procured prompts - "Model...

- id: art_01M5NGX94FDCQQDDYN8728J087
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T06, T07, T20 · tags: none
- updated: 2026-10-23T23:18:04.169Z
- url: https://veyrul.com/articles/art_01M5NGX94FDCQQDDYN8728J087

What it measures (R1): an Elo-like composite on OpenArt's own Arena, anchored at MiniMax H3 = 1,000; weights 30% general capabilities, 17.5% talking, 17.5% singing, 17.5% multi-character speaker assignment, 17.5% multilingual. Outputs are generated by OpenArt from procured prompts - "Model providers cannot submit, select, or regenerate those outputs" - but OpenArt operates the arena and sells access to the ranked models, so the post itself says it "should not be described as an independent third party". Scores are relative within this board only; no confidence intervals are printed, so the 6-point Seedance 2.0 vs 2.0 Mini gap is not a demonstrated difference. Wan 3.0 is second on the same snapshot's Video Overall but last here - a general video ranking is a poor proxy for dialogue work. Scope gap: only five native audio+video generators are ranked; dedicated lip-replacement (sync, VEED, HeyGen, LatentSync) and image+audio avatar models (OmniHuman, InfiniTalk, Fabric) are absent, so ...

What it measures (R1): an Elo-like composite on OpenArt's own Arena, anchored at MiniMax H3 = 1,000; weights 30% general capabilities, 17.5% talking, 17.5% singing, 17.5% multi-character speaker assignment, 17.5% multilingual. Outputs are generated by OpenArt from procured prompts - "Model providers cannot submit, select, or regenerate those outputs" - but OpenArt operates the arena and sells access to the ranked models, so the post itself says it "should not be described as an independent third party". Scores are relative within this board only; no confidence intervals are printed, so the 6-point Seedance 2.0 vs 2.0 Mini gap is not a demonstrated difference. Wan 3.0 is second on the same snapshot's Video Overall but last here - a general video ranking is a poor proxy for dialogue work. Scope gap: only five native audio+video generators are ranked; dedicated lip-replacement (sync, VEED, HeyGen, LatentSync) and image+audio avatar models (OmniHuman, InfiniTalk, Fabric) are absent, so it cannot settle the task-(a)/(b) choices in C3-B502-01; Veo 3 is also absent. Useful method content: native generation couples timing and mouth shape (each retry changes both), while post-dubbing keeps the preferred visual take but does not demonstrate native sync; polished demos may hide audio replacement. Named failure modes and tests: mouth drift on long lines or heavy motion (one short line per shot, frontal/three-quarter face), wrong speaker in multi-character scenes (label speakers, alternate short lines), incorrect mouth shapes across languages (fix language and accent labels), changed lyrics when singing, music masking speech in ads, and voice changes between connected film shots. Suggested screening protocol: five generations per task, identical settings, equal tuning budget, score original exports for phoneme alignment, facial stability, speaker assignment, voice quality, artefacts and script fidelity.

Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Leaderboard snapshot; date, vote counts and judge type not shown; operator-generated outputs.

Limitations: Snapshot date not printed on the page; vote counts, judge type (human vs model) and confidence intervals not shown; operator conflict of interest. Compare with Arena.ai and Artificial Analysis video boards (C3-B366-01, C3-B438-01), which use different populations.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://openart.ai/blog/openart-arena-lip-sync-ranking/",
      "note": "TL;DR table; What the ranking does and doesn't prove; How the Lip Sync board is scored"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] What it measures (R1): an Elo-like composite on OpenArt's own Arena, anchored at MiniMax H3 = 1,000; weights 30% general capabilities, 17.5% talking, 17.5% singing, 17.5% multi-character speaker assignment, 17.5% multilingual. Outputs are generated by OpenArt from procured prompts - "Model providers cannot submit, select, or regenerate those outputs" - but OpenArt operates the arena and sells access to the ranked models, so the post itself says it "should not be described as an independent third party". Scores are relative within this board only; no confidence intervals are printed, so the 6-point Seedance 2.0 vs 2.0 Mini gap is not a demonstrated difference. Wan 3.0 is second on the same snapshot's Video Overall but last here - a general video ranking is a poor proxy for dialogue work. Scope gap: only five native audio+video generators are ranked; dedicated lip-replacement (sync, VEED, HeyGen, LatentSync) and image+audio avatar models (OmniHuman, InfiniTalk, Fabric) are absent, so it cannot settle the task-(a)/(b) choices in C3-B502-01; Veo 3 is also absent. Useful method content: native generation couples timing and mouth shape (each retry changes both), while post-dubbing keeps the preferred visual take but does not demonstrate native sync; polished demos may hide audio replacement. Named failure modes and tests: mouth drift on long lines or heavy motion (one short line per shot, frontal/three-quarter face), wrong speaker in multi-character scenes (label speakers, alternate short lines), incorrect mouth shapes across languages (fix language and accent labels), changed lyrics when singing, music masking speech in ads, and voice changes between connected film shots. Suggested screening protocol: five generations per task, identical settings, equal tuning budget, score original exports for phoneme alignment, facial stability, speaker assignment, voice quality, artefacts and script fidelity. · locator: TL;DR table; What the ranking does and doesn't prove; How the Lip Sync board is scored · source: https://openart.ai/blog/openart-arena-lip-sync-ranking/

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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