minimax
/
video-01-director
Generate videos with specific camera movements
- Public
- 23.6K runs
-
$0.50 per video
-
Commercial use
Prediction
minimax/video-01-directorOfficial modelID654gq25cfxrmc0cmyjev7cz4rgStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- [Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.
- prompt_optimizer
{ "prompt": "[Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.", "prompt_optimizer": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "[Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.", prompt_optimizer: true }; const output = await replicate.run("minimax/video-01-director", { input }); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "minimax/video-01-director", input={ "prompt": "[Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.", "prompt_optimizer": True } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "input": { "prompt": "[Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.", "prompt_optimizer": true } }' \ https://api.replicate.com/v1/models/minimax/video-01-director/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-11T10:48:37.954149Z", "created_at": "2025-02-11T10:46:01.599000Z", "data_removed": false, "error": null, "id": "654gq25cfxrmc0cmyjev7cz4rg", "input": { "prompt": "[Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.", "prompt_optimizer": true }, "logs": "Moderating content...\nModeration complete in 0.20sec\nRunning prediction... \nInitializing video generation with prompt: [Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky.\nUsing model: T2V-01-Director\nGenerating video...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nGenerated video in 153.9sec\nRetrieving video...\nDownloading 2694007 bytes\nDownloaded 2.57MB in 2.22sec", "metrics": { "predict_time": 156.35274661, "total_time": 156.355149 }, "output": "https://replicate.delivery/xezq/knaWYKDx91IUBRvuWsvm4NKMCwLqhIeO4oUkFuwIVTyC6GHKA/tmpncofyycj.output.mp4", "started_at": "2025-02-11T10:46:01.601402Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-rswgdnmdooumkq5dkewprcuvnuf3r2lw7h5frjmtoq66q4r6of6a", "get": "https://api.replicate.com/v1/predictions/654gq25cfxrmc0cmyjev7cz4rg", "cancel": "https://api.replicate.com/v1/predictions/654gq25cfxrmc0cmyjev7cz4rg/cancel" }, "version": "hidden" }
Generated inModerating content... Moderation complete in 0.20sec Running prediction... Initializing video generation with prompt: [Pull out, Tilt up] A knight stands amid ruins holding a broken sword, the camera revealing burning city walls and a massive dragon shadow in the sky. Using model: T2V-01-Director Generating video... Still generating... Still generating... Still generating... Still generating... Generated video in 153.9sec Retrieving video... Downloading 2694007 bytes Downloaded 2.57MB in 2.22sec
Prediction
minimax/video-01-directorOfficial modelIDqm3j4a3q39rm80cmyjerrcr4qmStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- [Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.
- prompt_optimizer
{ "prompt": "[Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.", "prompt_optimizer": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "[Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.", prompt_optimizer: true }; const output = await replicate.run("minimax/video-01-director", { input }); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "minimax/video-01-director", input={ "prompt": "[Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.", "prompt_optimizer": True } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "input": { "prompt": "[Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.", "prompt_optimizer": true } }' \ https://api.replicate.com/v1/models/minimax/video-01-director/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-11T10:48:24.857392Z", "created_at": "2025-02-11T10:45:47.930000Z", "data_removed": false, "error": null, "id": "qm3j4a3q39rm80cmyjerrcr4qm", "input": { "prompt": "[Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.", "prompt_optimizer": true }, "logs": "Moderating content...\nModeration complete in 0.17sec\nRunning prediction... \nInitializing video generation with prompt: [Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky.\nUsing model: T2V-01-Director\nGenerating video...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nGenerated video in 154.7sec\nRetrieving video...\nDownloading 1633369 bytes\nDownloaded 1.56MB in 2.04sec", "metrics": { "predict_time": 156.924634121, "total_time": 156.927392 }, "output": "https://replicate.delivery/xezq/fREgAIFsael1Y0ul4gIT5wJbI7bEIyI5M4NeNVRGBLtxnbcoA/tmpw3ej0xau.output.mp4", "started_at": "2025-02-11T10:45:47.932758Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-4izbfqcnqsacu5kyylvrd3rlkaxwajlbrssvfan5woqhelfsroxq", "get": "https://api.replicate.com/v1/predictions/qm3j4a3q39rm80cmyjerrcr4qm", "cancel": "https://api.replicate.com/v1/predictions/qm3j4a3q39rm80cmyjerrcr4qm/cancel" }, "version": "hidden" }
Generated inModerating content... Moderation complete in 0.17sec Running prediction... Initializing video generation with prompt: [Pan left, Tilt up] Starting from a small rabbit looking upward, following its gaze to a bright red balloon floating into the sky. Using model: T2V-01-Director Generating video... Still generating... Still generating... Still generating... Still generating... Generated video in 154.7sec Retrieving video... Downloading 1633369 bytes Downloaded 1.56MB in 2.04sec
Prediction
minimax/video-01-directorOfficial modelIDb9fhh58dgsrm80cmyjevahz9ecStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- [Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.
- prompt_optimizer
{ "prompt": "[Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.", "prompt_optimizer": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "[Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.", prompt_optimizer: true }; const output = await replicate.run("minimax/video-01-director", { input }); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "minimax/video-01-director", input={ "prompt": "[Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.", "prompt_optimizer": True } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "input": { "prompt": "[Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.", "prompt_optimizer": true } }' \ https://api.replicate.com/v1/models/minimax/video-01-director/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-11T10:47:55.890605Z", "created_at": "2025-02-11T10:45:20.902000Z", "data_removed": false, "error": null, "id": "b9fhh58dgsrm80cmyjevahz9ec", "input": { "prompt": "[Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.", "prompt_optimizer": true }, "logs": "Moderating content...\nModeration complete in 0.17sec\nRunning prediction... \nInitializing video generation with prompt: [Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey.\nUsing model: T2V-01-Director\nGenerating video...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nGenerated video in 153.9sec\nRetrieving video...\nDownloading 4639417 bytes\nDownloaded 4.42MB in 0.84sec", "metrics": { "predict_time": 154.985901682, "total_time": 154.988605 }, "output": "https://replicate.delivery/xezq/GQfMU5XRHkTLeE9usLSX5jePxj4HI8jQPgwwbjoXlsn2mbcoA/tmpu80eypdh.output.mp4", "started_at": "2025-02-11T10:45:20.904704Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-qwsetvrxfhfvr45tc7tek3f7iocwbruarujzowvzmmqaqz2lb72a", "get": "https://api.replicate.com/v1/predictions/b9fhh58dgsrm80cmyjevahz9ec", "cancel": "https://api.replicate.com/v1/predictions/b9fhh58dgsrm80cmyjevahz9ec/cancel" }, "version": "hidden" }
Generated inModerating content... Moderation complete in 0.17sec Running prediction... Initializing video generation with prompt: [Tracking shot] A red fox moves stealthily through autumn woods, hunting for prey. Using model: T2V-01-Director Generating video... Still generating... Still generating... Still generating... Still generating... Generated video in 153.9sec Retrieving video... Downloading 4639417 bytes Downloaded 4.42MB in 0.84sec
Prediction
minimax/video-01-directorOfficial modelIDh6rvg5dayxrm80cmyjebgk7k68StatusSucceededSourceWebTotal durationCreatedInput
- prompt
- A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]
- prompt_optimizer
{ "prompt": "A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]", "prompt_optimizer": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]", prompt_optimizer: true }; const output = await replicate.run("minimax/video-01-director", { input }); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "minimax/video-01-director", input={ "prompt": "A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]", "prompt_optimizer": True } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "input": { "prompt": "A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]", "prompt_optimizer": true } }' \ https://api.replicate.com/v1/models/minimax/video-01-director/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-11T10:47:32.300915Z", "created_at": "2025-02-11T10:44:55.671000Z", "data_removed": false, "error": null, "id": "h6rvg5dayxrm80cmyjebgk7k68", "input": { "prompt": "A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]", "prompt_optimizer": true }, "logs": "Moderating content...\nModeration complete in 0.34sec\nRunning prediction... \nInitializing video generation with prompt: A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot]\nUsing model: T2V-01-Director\nGenerating video...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nGenerated video in 153.4sec\nRetrieving video...\nDownloading 1061297 bytes\nDownloaded 1.01MB in 2.88sec", "metrics": { "predict_time": 156.627711713, "total_time": 156.629915 }, "output": "https://replicate.delivery/xezq/CkqhPSD1OhpRPla5JyIhjMWVGvnqfgfyRhDYmKgWnwUEzNOUA/tmpnm79zs_y.output.mp4", "started_at": "2025-02-11T10:44:55.673203Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-6ngm5gajlucvqahdblchiplbduhkykqa7egb4bds7ziecdnhya5q", "get": "https://api.replicate.com/v1/predictions/h6rvg5dayxrm80cmyjebgk7k68", "cancel": "https://api.replicate.com/v1/predictions/h6rvg5dayxrm80cmyjebgk7k68/cancel" }, "version": "hidden" }
Generated inModerating content... Moderation complete in 0.34sec Running prediction... Initializing video generation with prompt: A man picks up a leather-bound book from a dusty shelf [Pedestal up], then begins reading it by candlelight [Static shot] Using model: T2V-01-Director Generating video... Still generating... Still generating... Still generating... Still generating... Generated video in 153.4sec Retrieving video... Downloading 1061297 bytes Downloaded 1.01MB in 2.88sec
Prediction
minimax/video-01-directorOfficial modelIDk9jcyx3yksrm80cmyje80q2jggStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined.
- prompt_optimizer
{ "prompt": "Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined.", "prompt_optimizer": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined.", prompt_optimizer: true }; const output = await replicate.run("minimax/video-01-director", { input }); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "minimax/video-01-director", input={ "prompt": "Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined.", "prompt_optimizer": True } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "input": { "prompt": "Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman\'s face, dirt-streaked but determined.", "prompt_optimizer": true } }' \ https://api.replicate.com/v1/models/minimax/video-01-director/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-11T10:47:20.854258Z", "created_at": "2025-02-11T10:44:44.318000Z", "data_removed": false, "error": null, "id": "k9jcyx3yksrm80cmyje80q2jgg", "input": { "prompt": "Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined.", "prompt_optimizer": true }, "logs": "Moderating content...\nModeration complete in 0.18sec\nRunning prediction... \nInitializing video generation with prompt: Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined.\nUsing model: T2V-01-Director\nGenerating video...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nGenerated video in 153.5sec\nRetrieving video...\nDownloading 2447177 bytes\nDownloaded 2.33MB in 2.81sec", "metrics": { "predict_time": 156.532761601, "total_time": 156.536258 }, "output": "https://replicate.delivery/xezq/IQN7fgwjt7TfMEaPGDzy7btRgBOdh5xVQk4yXk3Gzmp4yNOUA/tmpcbet09kk.output.mp4", "started_at": "2025-02-11T10:44:44.321496Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-3ub6torzec6znq3xbxmozhoys6nlbxtviwa424652snjbvnnyhpq", "get": "https://api.replicate.com/v1/predictions/k9jcyx3yksrm80cmyje80q2jgg", "cancel": "https://api.replicate.com/v1/predictions/k9jcyx3yksrm80cmyje80q2jgg/cancel" }, "version": "hidden" }
Generated inModerating content... Moderation complete in 0.18sec Running prediction... Initializing video generation with prompt: Above an ancient battlefield [Pan right, Pedestal down], a close-up reveals a warrior woman's face, dirt-streaked but determined. Using model: T2V-01-Director Generating video... Still generating... Still generating... Still generating... Still generating... Generated video in 153.5sec Retrieving video... Downloading 2447177 bytes Downloaded 2.33MB in 2.81sec
Prediction
minimax/video-01-directorOfficial modelIDdgwff0azaxrme0cn7hjb5ek5agStatusSucceededSourceWebTotal durationCreatedInput
{ "prompt": "[truck left, pan right, tracking shot] bullet time effect", "prompt_optimizer": true, "first_frame_image": "https://replicate.delivery/pbxt/MYlgrLz3fkaOdsOpAY4H0ugeGkhJaZj2AM3LrzChrRA2FSyt/MemeLoveTriangle_297886754.webp" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "[truck left, pan right, tracking shot] bullet time effect", prompt_optimizer: true, first_frame_image: "https://replicate.delivery/pbxt/MYlgrLz3fkaOdsOpAY4H0ugeGkhJaZj2AM3LrzChrRA2FSyt/MemeLoveTriangle_297886754.webp" }; const output = await replicate.run("minimax/video-01-director", { input }); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "minimax/video-01-director", input={ "prompt": "[truck left, pan right, tracking shot] bullet time effect", "prompt_optimizer": True, "first_frame_image": "https://replicate.delivery/pbxt/MYlgrLz3fkaOdsOpAY4H0ugeGkhJaZj2AM3LrzChrRA2FSyt/MemeLoveTriangle_297886754.webp" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run minimax/video-01-director using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "input": { "prompt": "[truck left, pan right, tracking shot] bullet time effect", "prompt_optimizer": true, "first_frame_image": "https://replicate.delivery/pbxt/MYlgrLz3fkaOdsOpAY4H0ugeGkhJaZj2AM3LrzChrRA2FSyt/MemeLoveTriangle_297886754.webp" } }' \ https://api.replicate.com/v1/models/minimax/video-01-director/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-25T09:19:19.924121Z", "created_at": "2025-02-25T09:16:05.847000Z", "data_removed": false, "error": null, "id": "dgwff0azaxrme0cn7hjb5ek5ag", "input": { "prompt": "[truck left, pan right, tracking shot] bullet time effect", "prompt_optimizer": true, "first_frame_image": "https://replicate.delivery/pbxt/MYlgrLz3fkaOdsOpAY4H0ugeGkhJaZj2AM3LrzChrRA2FSyt/MemeLoveTriangle_297886754.webp" }, "logs": "Moderating content...\nModerating content...\nModeration complete in 0.25sec\nModeration complete in 1.07sec\nRunning prediction... \nInitializing video generation with prompt: [truck left, pan right, tracking shot] bullet time effect\nUsing model: I2V-01-Director\nGenerating video...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nStill generating...\nGenerated video in 190.7sec\nRetrieving video...\nDownloading 1372023 bytes\nDownloaded 1.31MB in 2.27sec", "metrics": { "predict_time": 194.071953067, "total_time": 194.077121 }, "output": "https://replicate.delivery/xezq/UpqkYwl7hTqTJ5rfIE0eb5WpDv6quG6PeFcdtH157Y2uonloA/tmp2dc62s6m.output.mp4", "started_at": "2025-02-25T09:16:05.852168Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-n65zwdrxs2dhpvhbn543ro26fjcgj22r6stbgussmocrys6rzepq", "get": "https://api.replicate.com/v1/predictions/dgwff0azaxrme0cn7hjb5ek5ag", "cancel": "https://api.replicate.com/v1/predictions/dgwff0azaxrme0cn7hjb5ek5ag/cancel" }, "version": "hidden" }
Generated inModerating content... Moderating content... Moderation complete in 0.25sec Moderation complete in 1.07sec Running prediction... Initializing video generation with prompt: [truck left, pan right, tracking shot] bullet time effect Using model: I2V-01-Director Generating video... Still generating... Still generating... Still generating... Still generating... Still generating... Generated video in 190.7sec Retrieving video... Downloading 1372023 bytes Downloaded 1.31MB in 2.27sec
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