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Runway Aleph 2.0

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Runway Aleph 2.0 is a closed-weights video model from Runway, released May 2026. Licence: proprietary.

Catalogue identity notes

Runway's second-generation in-context video editing model (announced 21 May 2026 with Edit Studio), served on the Runway API as aleph2. Distinct from runway-aleph (Gen-4 Aleph, 2025-07). The WROP paper ran 'Runway Aleph 2' through the Runway API as a frame-wise edit/transfer model.

Model information sources

Release date ↗

65.3±6.7#22 of 93 video modelsfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The video models ranked either side of Runway Aleph 2.0, out of 139 with a score, then more from Runway.

#modelscorewhereRAMreleased
24Vidu Q3 Pro ShengShu (Vidu)65±2api $0.10/sec2026-01
25Veo 3 Fast Google65±2comparison only2025-07
26Runway Aleph 2.0 Runway65±7api $0.28/sec2026-05
27Sora 2 OpenAI65±2comparison only2025-10
28Wan 2.6 Alibaba65±1api $0.10/sec2025-12
more from Runway
36Runway Gen-4.5 Runway58±2api $0.12/sec2025-12
41Runway Aleph Runway56±5comparison only2025-07
68Runway Gen-4 Runway50±4comparison only2025-03

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

$ what it's good at

other tests1 not in a task · 81% of its score
testresultvs the others in its rundifficultycountswhy
WROP object-permanence exam (human Elo)1518.3 ✎▄····██···▄█ beats 4/7avg 1299▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 81%noisy

$ where to run it

Through an API

api · $0.28/sec · docs.dev.runwayml.com ↗ · price sourceUSD per second of output video on the Runway developer API. Product: Runway API video-to-video. API model: aleph2 (listed as 'Aleph 2.0'). Price basis: 28 credits per second × $0.01 per credit; 56-credit minimum per generation. Professional/HDR output formats (prores, png_sequence, 10-bit/HDR profiles) add 5–40 credits per second; sales tax excluded. Currency: USD. Runway API pricing documentation, observed 2026-10-09.

$ how the score was worked out · Training Object Permanence in… 81%

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
Training Object Permanence in World Models (WROP exam; arXiv:2609.28654v1)1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 81%CC-BY-4.0
prior · pull toward the middle▇▇▇▇▇▇ 19%
weighted average= 65.3

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data updated · sources and licences · json