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Runway Gen-4.5

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Runway Gen-4.5 is a closed-weights video model from Runway, released December 2025. Licence: proprietary.

58.4±2.2#29 of 93 video modelsfrom 3 benchmark results across 3 sources

$ how it compares

The video models ranked either side of Runway Gen-4.5, out of 139 with a score, then more from Runway.

#modelscorewhereRAMreleased
34Kling 2.6 Pro Kuaishou (Kling AI)59±2api $0.070/sec2025-12
35PixVerse V5.6 PixVerse59±2api $0.045/sec2026-02
36Runway Gen-4.5 Runway58±2api $0.12/sec2025-12
37Wan 2.1 I2V Plus Alibaba58±5api price unknown2025-01
38Cosmos3-Super NVIDIA58±4local~160GB2026-05
more from Runway
26Runway Aleph 2.0 Runway65±7api $0.28/sec2026-05
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

text to video▆▄▃▄▆▅█▃▂▂▂▄ #19 of 68 * · 81% of its score · 1 test

Beats Kling 2.6 Pro here, though they rank higher overall. Trails Seedance 1.5 Pro here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LMArena video1224.7 ✎▂▂▃▆█▆·▆▅▁▂▇ beats 20/41avg 1147▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 81%typical
image to video▁▂·▂▅█▅▄▅▆▃▄ #18 of 50 * · 8.9% of its score · 1 test

Beats HappyHorse 1.1, Vidu Q3 Pro, Wan 2.6 here, though they rank higher overall.

testresultvs the others in its rundifficultycountswhy
VGI-Bench visual reasoning (I2V)36.6% ✎▄▄···▄▄█·█·▄ beats 4/8hard · avg 20%▇▇▇▇ 8.9%at its level
other tests1 not in a task · 8.5% of its score
testresultvs the others in its rundifficultycountswhy
SWITCH interactive-interface I2V (VLM-judge overall)36.0% ✎███··█·····█ beats 1/4very hard · avg 28%▇▇▇ 8.5%typical

$ where to run it

Through an API

api · $0.12/sec · docs.dev.runwayml.com ↗ · price sourceUSD per generated second, standard Gen-4.5 output. 12 credits × USD0.01/credit; professional/HDR format surcharges and sales tax excluded. Product: Runway developer API. API model: gen4.5. Settings: output format=standard, prores=no, hdr=no. Price basis: published rate. Currency: USD.

$ how the score was worked out · LMArena leaderboard dataset 81%, VGI-Bench: Probing Visual Int… 9%, SWITCH: Benchmarking Modeling… 8%

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
LMArena leaderboard dataset1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 81%CC BY 4.0
VGI-Bench: Probing Visual Intelligence in Video Generation Models1▇▇▇ 9%CC-BY-4.0
SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios (arXiv:2511.17649v5)1▇▇▇ 8%CC-BY-SA-4.0
prior · pull toward the middle▇ 2%
weighted average= 58.4

$ 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