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Luma Dream Machine 1.6

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Luma Dream Machine 1.6 is a closed-weights video model from Luma AI, released September 2024. Licence: proprietary.

Catalogue identity notes

Dream Machine 1.6 (announced 4 Sep 2024 with camera motion); labelled 'luma-1.6' by WorldModelBench. Not in Luma's current API (ray-2, ray-flash-2).

50.0±7.3comparison only: no current run option verifiedfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The video models ranked either side of Luma Dream Machine 1.6, out of 139 with a score, then more from Luma AI.

#modelscorewhereRAMreleased
64Kandinsky 6.0 Video Lite Sber51±7local~34GB2026-10
65Seaweed-7B ByteDance Seed50±6comparison only2025-04
66Luma Dream Machine 1.6 Luma AI50±7comparison only2024-09
67Wan 2.2 A14B Alibaba50±2api $0.080/sec +local~31GB2025-07
68Runway Gen-4 Runway50±4comparison only2025-03
more from Luma AI
49Ray 3 Luma AI55±2comparison only2025-09
94Ray 2 Luma AI43±2comparison only2025-01
97Luma Dream Machine 1.0 Luma AI42±7comparison only2024-06

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

$ what it's good at

other tests1 not in a task · 77% of its score
testresultvs the others in its rundifficultycountswhy
WorldModelBench (human total)7.72 / 10 ✎▅··▅▃···▃··█ beats 8/8easy · avg 7.71 / 10▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 77%typical

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · WorldModelBench: Judging Vide… 77%

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
WorldModelBench: Judging Video Generation Models As World Models1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 77%CC-BY-4.0
prior · pull toward the middle▇▇▇▇▇▇▇ 23%
weighted average= 50.0

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

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