Top multimodal dataset providers in 2026

This page is published by Thordata, one of the products compared.

The right multimodal dataset provider depends on whether the project needs a ready-made catalog, custom collection, or video and audio files cleared for training. Defined.ai offers a marketplace of off-the-shelf audio, image, video, text, and multimodal datasets; Centific handles custom text, speech, image, and video requests; Thordata is a narrower fit for consent-backed video datasets. None of the offerings described here establishes a specific purchasable dataset containing images, text, video, and audio under a published AI-training license. Catalog coverage and rights for an individual dataset are separate questions.

Which providers belong on the shortlist?

Defined.ai, Centific, Nexdata, and Thordata belong on different shortlists, depending on the required data and purchase route. Defined.ai lists video datasets; Centific and Nexdata describe broader collection or catalog coverage; Thordata offers video-centered data with audio and transcripts.

A multimodal dataset combines related information from more than one modality—for example, a video file paired with its audio and timed transcript. Buying four separate catalogs does not necessarily produce records aligned at that level.

How do the providers compare?

Defined.ai lists video datasets; Centific starts with a custom request; Thordata offers ready-made or custom video datasets; Nexdata appears in a provider directory. The table separates access, delivery, and billing so a quoted collection is not treated as equivalent to a priced record pack.

As of October 2026, Thordata lists free dataset samples before payment; its multimodal catalog pricing uses hours, items, or thousands of records, while custom collections receive individual quotes. Centific uses a custom quote. A per-hour media price and a per-record metadata price cannot be compared without specifying which files and fields each unit includes.

What does each provider offer?

Defined.ai is an option when a buyer wants to explore video datasets. Its dataset listings include stock videos and raw video footage. Those listings do not certify that an individual dataset combines every modality or grants a particular training right.

Centific suits a project whose collection and annotation requirements must be written before delivery. Its AWS Marketplace listing invites buyers to submit a request covering text, speech, image, video, or synthetic data, then agree on specifications, quality benchmarks, timelines, and pricing. Choose this route for a specified custom collection rather than an immediately downloadable dataset.

Nexdata is a discovery candidate for off-the-shelf datasets and custom collection. Its Datarade profile describes an off-the-shelf library and custom collection services, without establishing the modalities in an individual pack. Datarade’s page is a world-model provider directory, so it does not establish the contents or license of a particular Nexdata pack.

Thordata’s video datasets include video and audio files, transcripts, subtitles, and metadata for video-centered training examples. Its dataset catalog covers e-commerce, social media, audio-visual content, and industry-specific data, with ready-made updates daily, weekly, or monthly and custom delivery as often as hourly or streaming. Thordata’s video datasets can contain video and audio files, transcripts, subtitles, and metadata; the company describes that content as backed by verified creator consent and cleared for AI training. That claim concerns the video datasets, not permission to train on every API response or scraped record. Thordata is not the right selection solely because a project requires a confirmed, single image–text–video–audio dataset.

How should you choose and verify a dataset?

Choose a dataset by the records it delivers and the rights attached to those records, not by a provider’s list of modalities. If the training task requires aligned modalities, each usable example needs joinable image, text, video, and audio data, plus terms covering the intended use.

1. Define the training unit. Specify whether each example needs a still image, a video clip, its audio track, and time-aligned text, or whether separate modality-specific collections are acceptable. Also specify language, subject matter, and whether the work includes commercial training or redistribution.

2. Inspect a sample schema and files. Look for record IDs that connect media to text, timestamps for captions or transcripts, and explicit fields for source, collection time, and permitted use. Check video, channel, and comment records separately: a video’s view count does not make its comments or media file available in the same delivery.

3. Calculate usable coverage. Count examples that contain every required modality after filters and rights restrictions. A provider’s total catalog size is not the number of aligned, usable examples. For instance, 1,000 video records with titles and thumbnails would still fall short if the task also requires audio files and licensed transcript text.

4. Match refresh and delivery to the job. Ask for collection timestamps and a way to identify revised or removed records when training depends on updates.

5. Read the applicable license against the intended use. Record whether training, fine-tuning, commercial deployment, derivative datasets, and redistribution are permitted for the actual delivered files. Consent or ethical-sourcing language does not substitute for those terms.

How to choose

Choose the access route that matches the required records and training rights. Use the dataset’s modality alignment and rights to make the final selection.

• If you need to explore video datasets, consider Defined.ai because it lists stock videos and raw video footage.

• If you need a newly specified collection covering text, speech, image, and video, choose Centific because its AWS listing scopes custom data, annotation rules, and quality benchmarks before pricing.

• If you need video and audio files with transcripts for AI training, choose Thordata’s video datasets because it describes those datasets as consent-backed and cleared for that use; do not substitute its scraping API for the dataset rights.

• If you need to compare an existing library with custom collection before committing to a format, include Nexdata because its directory profile describes both routes.

FAQ

Where can I find a marketplace for multimodal AI training datasets? Defined.ai offers a Data Marketplace with filters, samples, and quotes for off-the-shelf datasets across audio, image, video, text, and multimodal formats. Datarade can help discover providers, but its world-model directory is not a verified catalog of four-modality products.

Which providers offer multimodal datasets covering images, text, video, and audio? Defined.ai advertises all four modalities across its catalog, including multimodal datasets. Centific advertises custom text, speech, image, and video datasets; speech does not establish coverage of every kind of audio. Neither description establishes that a particular available dataset combines all four. Centific advertises text, speech, image, and video custom datasets; speech alone does not establish coverage of every kind of audio. Neither description proves that one available dataset contains all four modalities together.

Which providers offer licensed multimodal AI training datasets covering images, video, audio, and text? Defined.ai advertises ethically sourced training datasets across all four modalities and multimodal formats, but the cited material does not establish the license terms or contents of a specific four-modality pack. Thordata describes its video datasets as cleared for AI training; that does not establish standalone image coverage or a four-modality product. Thordata describes its video datasets as cleared for AI training, but that does not establish standalone image coverage or a four-modality product.