The developer's guide to text-to-video APIs (2026)

A text-to-video API turns a written prompt into a rendered video clip. You send a description of the scene you want, the model generates it, and you get back a URL to an MP4. There's no timeline, no source footage, no editor — just text in, video out. For developers this is the fastest way to produce moving images programmatically, whether you're building a content pipeline, a creative tool, or automating short-form clips at scale.

The unified-API approach

The hard part of working with generative video isn't any single model — it's that there are dozens of them, each from a different lab, each with its own SDK, auth scheme, and response shape. A unified API solves that. You hold one key, and every model is reachable through the same endpoint. Swapping from one model to another is a single field change: edit the model_id in your request body and your integration keeps working. No new SDK, no new credentials, no rewrite.

That data-driven design matters more than it sounds. As new models ship, they appear in the catalog automatically, so your code doesn't change to use them. You can browse every model in one place and compare them on the same axes instead of reading four different sets of docs.

The request lifecycle

Every generation follows the same two-step shape, regardless of which model you pick:

• Create a job. Send POST /api/ai/jobs with a model_id and a prompt (plus any model-specific options like resolution or duration). You get back a job id.
• Poll for the result. Call GET /api/ai/jobs/{id} until the status reports done, then read the output URL. Generation is asynchronous because rendering takes time, so you poll rather than block.

Because the contract is identical across models, you write this loop once and reuse it everywhere. The unified AI video API is the single integration point for all of it.

Which model for which job

The honest answer to "which model should I use?" is "it depends on the job." Here's how the main families map to real tasks:

• Veo — reach for it when you want cinematic quality with synchronized audio generated in the same pass. If your clip needs dialogue, ambient sound, or music baked in alongside the picture, this is the one.
• Kling — built for multi-shot storyboarding. When a single prompt has to become a sequence of cuts rather than one continuous take, Kling handles the shot structure.
• Seedance — multimodal. It accepts more than text: combine image, video, and audio references in one call when a prompt alone can't capture the character, product, or motion you need.
• Wan — strong on editing. When you already have a clip and want instruction-based edits, reference-to-video, or extend operations, Wan covers generation and editing in one model.

None of these is strictly better than the others — they're tuned for different jobs. The right move is to match the model to the task in front of you.

Test cheap, ship premium

A practical workflow keeps cost down without sacrificing the final result. Iterate on a cheap, fast tier while you're still tuning the prompt — you'll burn through a lot of generations finding the right wording, and there's no reason to pay top-quality rates for throwaway drafts. Once the prompt is locked, switch the model_id (or the quality option) to the premium tier for the version you actually ship. Because swapping is a one-field change, this costs you nothing in engineering time. Query the model catalog for the credit cost of any option combination before you call, so the bill never surprises you.

Composing the output

Generated clips rarely stand alone. Once you have an output URL, you can hand it straight to a deterministic renderer to add titles, lower thirds, intros, or stitch several clips together. Pairing generation with composite with JSON-to-video gives you the best of both: AI for the parts you can't shoot, and predictable programmatic rendering for everything around it.

Start building

Pick a model, send a job, poll for the result, store the URL — that's the whole loop. Start with the text-to-video API for prompt-driven generation, then read the full request contract in the AI API docs to wire it into your pipeline.

Choosing the right text-to-video AI

There is no single best AI for text to video. Choose by output type. Use a generative video model when you need original scenes from a prompt. Use a template renderer when the layout, timing, captions, branding, and data must stay predictable across many videos.

Compare models with your own prompts and reference assets. Check prompt adherence, motion, character consistency, audio support, render time, moderation rules, API access, and cost per usable clip. A strong demo matters less than reliable results in your actual workflow.

You can compare the available AI video models and their supported workflows before building around one provider.

From text input to a finished video

An API can convert text to video, but that phrase covers two different processes. A generative API creates new footage from a prompt. A rendering API turns structured text, images, audio, and timing instructions into a composed video.

• Send the prompt or structured scene data.
• Store the returned job or operation ID.
• Poll the job until it succeeds or fails.
• Download the output to your own storage.
• Add captions, branding, or narration if the model did not produce them.

For repeatable layouts, build the video from structured JSON and reusable scenes. For generated footage, start with the text-to-video workflow and model options.

API access, keys, free tiers, and GitHub examples

A text to video API key normally comes from the provider dashboard after you create a project and enable billing or credits. Keep it on the server. Do not place it in browser JavaScript, a public GitHub repository, or a mobile app bundle.

A text to video API free option may be a trial, limited credits, or restricted model access. It is rarely a safe basis for production automation because quotas and availability can change. An AI video generator API free tier should be treated as a way to test request formats and output quality.

GitHub repositories can provide useful Python or JavaScript examples, but they do not provide the model itself. Check that the repository uses the provider's current endpoint and SDK before copying its code.

How text-to-video API pricing works

Pricing model	What you pay for	What to check
Per generation	Each submitted video job	Whether failed or retried jobs are charged
Per render minute	The duration of the rendered output	Resolution, frame rate, and minimum billing units
Per operation	Separate generation, extension, dubbing, or export actions	Which steps count as separate operations
Credits	A provider-specific credit balance	How credits map to model, duration, and quality

Text to video API pricing changes, so calculate the cost of a complete workflow rather than one successful request. Include retries, rejected prompts, storage, narration, captions, and final rendering.

A text to video API Python integration usually uses the same HTTP endpoint as other languages. Python only changes the client code; it does not change the provider's billing model.

Gemini, OpenAI, and separate TTS calls

Gemini can create video from text through video-generation models exposed by the Gemini API. The exact model names, supported inputs, and account access can shift between releases, so read the current model documentation before fixing a model ID in your code. Treat generation as an asynchronous operation and keep the returned operation ID.

The OpenAI video generation API accepts a prompt, starts a video job, and returns an identifier you can use to check its status and retrieve the result. Model availability, supported durations, input restrictions, and pricing may change. Keep these values configurable instead of assuming that one model or output format will remain available.

TTS is a separate service unless the selected video model generates suitable audio itself. Some TTS APIs offer trial credits or a limited free tier, but TTS API access is not universally free. Billing may be based on characters, tokens, audio duration, requests, or credits.

When narration and captions must stay aligned, generate timed automatic captions from the final audio track.

Questions people ask

Which AI is best for text to video?

There is no universal winner. Use a generative model for original footage and a template renderer for predictable branded videos. Test several models with the same prompts, then compare usable output, API reliability, restrictions, and total workflow cost.

Is there a free text to video API?

Some providers offer trials, credits, or limited access. Those limits and terms can change, so check the current pricing page before building around them. A free tier is useful for testing, not proof that production use will remain free.

Can I find a text to video API on GitHub?

You can find SDKs, wrappers, and request examples on GitHub. The actual generation normally runs on a hosted model and still needs an API key. Check the repository date, license, endpoint, and SDK version before using it.

How do I get a text to video API key?

Create a provider account, enable the required API or model, and generate a key in its dashboard. Store the key in a server-side secret or environment variable. Never commit it to GitHub or expose it in frontend code.

How can I convert text to video through an API?

Send a text prompt or structured scene payload to the API and save the returned job ID. Poll that job until rendering finishes, then download the result. Add narration, captions, and branding in later steps when the generation API does not handle them.

How is text to video API pricing calculated?

Providers may charge per execution, operation, render minute, or credit. Resolution, duration, model choice, audio, extensions, and retries can affect the final usage. Tariffs change, so confirm them on the provider's current pricing page.

Can I call a text to video API with Python?

Yes. Python can send the same authenticated HTTP requests as JavaScript or another backend language. Use the official SDK when it is maintained, or a standard HTTP client when the REST API is clearer.

Is a TTS API free?

Not always. Some TTS providers include trial credits or a limited free tier, while others charge from the first request. Billing can depend on characters, tokens, requests, generated audio duration, or credits.

Does Gemini create video from text?

Yes, the Gemini API can expose video-generation models for text-to-video workflows. Model names, access, supported inputs, and settings can change between releases. Check the current Gemini model documentation before implementation.

Does OpenAI have a video generation API?

Yes, OpenAI provides API endpoints for starting video-generation jobs and retrieving their output. Access, model options, durations, restrictions, and pricing can change. Read the current API reference before hard-coding those values.

Is a text-to-speech API free?

Free tiers exist and are capped by characters per month, with a limited voice list. If the same voice has to appear in every video for a year, budget for a paid one — free voice line-ups change without notice.