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Runway Gen-4 Turbo

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Runway Gen-4 Turbo is a closed-weights video model from Runway, released April 2025.

Model information sources

Release date ↗

37.1±2.9#74 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 Gen-4 Turbo, out of 139 with a score, then more from Runway.

#modelscorewhereRAMreleased
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
111MAGI-1 4.5B Sand AI37±5comparison only2025-04
112LTX-2.3 Lightricks36±3api $0.040/sec +local~34GB2026-03
more from Runway
26Runway Aleph 2.0 Runway65±7api $0.28/sec2026-05
36Runway Gen-4.5 Runway58±2api $0.12/sec2025-12
41Runway Aleph Runway56±5comparison only2025-07

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

$ what it's good at

image to video▁▃·▂▅█▅▄▅▆▃▄ #49 of 50 * · 96% of its score · 1 test

Trails LTX-2.3 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Arena image-to-video1052.3 ✎▁▃▁▁▄▇▃▆▃▂▄█ beats 1/40avg 1189▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 96%typical

$ where to run it

Through an API

api · $0.050/sec · docs.dev.runwayml.com ↗ · price sourceUSD per second of generated video: Runway lists gen4_turbo at 5 credits per second; credits cost $0.01 each. Runway states one per-second rate for the model (no resolution tiers are listed). Product: Runway developer API video generation (image-to-video; gen4_turbo takes an image input). API model: gen4_turbo. Settings: standard mp4 output. Price basis: 5 credits × $0.01 per credit; sales tax excluded. Currency: USD. Runway official API pricing page, observed 2026-09-26.

$ how the score was worked out · LMArena leaderboard dataset 96%

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▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 96%CC BY 4.0
prior · pull toward the middle▇ 4%
weighted average= 37.1

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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