Write the script with a language model, voice it with text-to-speech, generate the shots with a video model and score it with a music model, all from one workspace. You still assemble the final timeline in a video editor, and this page shows which model fits each step and where the handoffs happen.
A short video is five jobs wearing one coat: someone writes it, someone speaks it, someone shoots it, someone scores it and someone captions it. Picasso IA puts a model for each of those jobs in one workspace, so you can run the whole chain in a single sitting instead of juggling five accounts. The honest part comes at the end: the pieces get assembled on a timeline in a video editor, not inside the toolkit.
Most people who try AI video start with the shots and stop there. The clips look good, the sound is missing or random, the pacing has no spine, and the result feels like a demo reel instead of a video. What is usually missing is a script that the other steps can follow. When the script comes first, the voice sets the length, the length sets how many shots you need, and the music has a runtime to match.
That is the real argument for chaining. Each step produces a file the next step consumes, and every handoff is a place where you decide something instead of hoping. Picasso IA holds 502 models, and the categories line up with the stages almost one to one: 75 large language models for the script, 24 text-to-speech models for the voice, 121 text-to-video models for the footage, 10 music generation models for the score and 3 speech-to-text models when you need a transcript. Everything runs in the toolkit, so the files never leave one tab until you export them.
New accounts get free credits, which is enough to run a short chain once and see where it holds. Each generation costs credits and the cost depends on the model and settings, so check the pricing page before planning a long series.
The table below maps each stage to the kind of model that does it, a few real examples from the catalog and what you carry into the next stage. The examples are starting points, not rankings; the full catalog has more in every row.
| Stage | Example models in the catalog | What it hands to the next step |
|---|---|---|
| Script and shot list | claude-sonnet-5, gemini-3.5-flash, gpt-5.4 | Narration text plus one line per shot |
| Voiceover | elevenlabs v3, minimax speech-2.8-hd, inworld tts-1.5-max | An audio file whose length sets the runtime |
| Footage | veo-3.1, kling-v3-video, seedance-2.0 | Short clips, one per shot |
| Music | lyria-3, minimax music-2.6, elevenlabs music | A track to sit under the narration |
| Captions | autocaption, gpt-4o-transcribe | Burned-in subtitles or a transcript file |
Two details in that table matter. First, some video models generate their own audio with the clip: veo-3.1 can produce a matched sound track, which is fine for ambience and a trap if you also add a voiceover, so switch it off or plan to mute it in the editor. Second, autocaption reads the audio of a finished video and burns the captions in, so it belongs at the very end of the chain, after you have assembled and exported the cut.
This is the order that avoids rework. It assumes a short video, something in the range of a minute, and a video editor of your choice for the last stretch.
If you want a deeper look at one stage, the pages on AI voiceover for videos, background music for videos and automatic video subtitles each go through that single step on its own.
A script written for reading on a page is the wrong script for this chain. The voice model will read every word literally, and the video model needs something it can picture. Ask the language model for two outputs at once: narration in short sentences you can say in one breath, and a shot list where each line describes one visual, one camera move and one setting, with no abstract phrases the video model cannot draw.
Keep the shot count honest. Video models produce short clips, a few seconds each, so a sixty second narration needs a dozen or more shots, not three. Ask for the shot list to be numbered and to say which narration line each shot covers. Then your editor timeline practically builds itself: line one, shot one, and so on.
Tip: generate the voiceover before the footage, not after. A voice file gives you real seconds to plan around, and it is far cheaper to adjust a shot list than to re-run clips because the narration turned out twice as long as you guessed.
When you write the music prompt, describe the feeling and the tempo instead of naming an artist or a song. Something like warm, light acoustic, steady and unhurried, no vocals, works across models and keeps the narration audible. For footage of people, stay with fictional characters or your own image, and for a voice, use one of the stock voices the models offer or your own recording; a real person's face or voice is not something to imitate without their consent.
Most failed chains fail at a handoff, not inside a model. These are the ones that come up most often:
The chain gets you the raw material, not the finished film. Picasso IA does not give you a multi-track timeline where voice, clips and music snap together, so the cut, the transitions, the audio levels and the final export all happen in a video editor. If you have never used one, budget time for that, and the Picasso IA vs CapCut page explains how the two differ.
There are other limits too. Continuity is the biggest: a character that looks right in one clip can drift in the next, and long scenes with the same actor across many shots take real effort even with reference images. Lip-synced talking heads need a dedicated lipsync model such as lipsync-2 on top of the voice, which adds another handoff. Precise on-screen text, logos and exact product shots are better filmed or designed, then animated, than generated from a description. And when a video needs one fixed look across a long series, a single template in an editor is simpler than re-running a chain for each episode.
If your goal is a quick explainer or a faceless channel, the chain fits well, as in AI explainer videos or faceless YouTube videos. If your goal is a one-take interview or a live event recap, film it.
You can make every ingredient there: the script, the voiceover, the clips, the music and the captions. What you cannot do is cut them together on a timeline, because the toolkit generates and edits individual files and does not assemble a multi-track project. Plan on exporting the pieces and finishing the cut in a video editor you already use.
There is no single right answer, which is why a catalog helps. For the script, claude-sonnet-5, gemini-3.5-flash and gpt-5.4 are all language models you can try on the same prompt. For voice, try elevenlabs v3 and minimax speech-2.8-hd. For footage, veo-3.1, kling-v3-video and seedance-2.0 are common starting points, and for music, lyria-3 and minimax music-2.6. Run the same input through two of them and keep whichever sounds or looks right.
Yes, for anything beyond a single clip. The editor is where narration, footage and music meet on a timeline, where you trim each shot to its narration line and set the audio levels. Any editor that accepts video and audio files will do. The tools on Picasso IA produce the parts, and the editor joins them.
Some can. veo-3.1 offers context-aware audio generated along with the clip, which suits ambience and short spoken moments. For a narrated video you will usually want a separate text-to-speech voice so you control the wording and the pacing, and then you mute or lower the built-in sound in the editor so the two do not compete.
Write one style sentence, covering lighting, color and camera feel, and paste it into every shot prompt. When a model accepts reference images, feed it the same one for each shot of a character or a product. Consistency is the hardest part of the whole chain, so check clips side by side before you commit to the edit; the page on consistent AI characters goes deeper on it.
It depends on the model and the settings you choose. veo-3.1, for example, offers short durations of a few seconds per generation. Most video models work in short clips, so a longer video is built from many shots rather than one long generation. Check each model's options in the toolkit before you write the shot list, so the number of shots matches the narration.
Use your own voice, or a stock voice from a text-to-speech model, or a fictional character. A recognizable real person's voice or face should not be cloned or imitated without that person's clear permission, and some platforms have rules about synthetic media that you should read before publishing. Picasso IA also has voice models for this, but consent and disclosure remain your responsibility.
Export your assembled video from the editor, upload that file to autocaption and choose the font, color and position. It transcribes the speech, burns the captions into the picture and gives you a transcript file you can correct and feed back in for a cleaner second run. If you only need the text, a speech-to-text model such as gpt-4o-transcribe works without touching the video.
Usually yes, but platforms change their rules on AI-generated media, disclosure labels and music use, so check the platform's current requirements before you upload. The same goes for any commercial use of the output. Keep the prompts and the exported files for each video in one folder so you can show what went into it if a platform or client asks.
Every step costs credits, and the price per generation depends on the model and the settings, so a figure here would go stale. Video clips generally cost more than text, voice or music, which means the shot count drives most of the bill. New accounts start with free credits, and current plans are on the pricing page.
Ready to try the first link? Open the Picasso IA toolkit, paste your idea into a language model and let it write the script that everything else follows.
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