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Vidu 1.5

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Vidu 1.5 is a closed-weights video model from ShengShu (Vidu), released November 2024. Licence: proprietary.

Catalogue identity notes

Released 13 Nov 2024 (PR Newswire). Vidu's current text-to-video API accepts viduq3-turbo, viduq3-pro, viduq2 and viduq1 only.

37.9±3.3comparison only: no current run option verifiedfrom 2 benchmark results across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The video models ranked either side of Vidu 1.5, out of 139 with a score, then more from ShengShu (Vidu).

#modelscorewhereRAMreleased
106Pandora (world model) Maitrix.org (MBZUAI / UC San Diego)39±7comparison only2024-05
107T2V-Turbo-v2 UC Santa Barbara38±5api price unknown +local~9.4GB2024-10
108Vidu 1.5 ShengShu (Vidu)38±3comparison only2024-11
109T2V-Turbo (VC2) UC Santa Barbara38±3local~9.4GB2024-05
110Runway Gen-4 Turbo Runway37±3api $0.050/sec2025-04
more from ShengShu (Vidu)
24Vidu Q3 Pro ShengShu (Vidu)65±2api $0.10/sec2026-01
47Vidu Q2 Turbo ShengShu (Vidu)55±3api $0.050/sec2025-09
54Vidu Q2 Pro ShengShu (Vidu)53±3comparison only2025-09

see all video models · find the ones that fit your machine

$ what it's good at

text to video▇▅▄▆█▆▇▂▃▃▂▄ #69 of 94 * · 95% of its score · 2 tests

Trails Pika 2.2, LTX-2.3, T2V-Turbo (VC2) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
AIGVE-60K human perception MOS (LOVE)54.6% ✎▄▄·█··█▄▄▄▄▄ beats 7/10easy · avg 73%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 61%at its level
AIGVE-60K human text-video correspondence MOS (LOVE)58.3% ✎▄▄·█▄█▄··▄▄▄ beats 9/10easy · avg 70%▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 35%at its level

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · LOVE: Benchmarking and Evalua… 95%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%CC-BY-4.0
prior · pull toward the middle▇ 5%
weighted average= 37.9

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Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json