AI Multimodal Model Comparison — which AI models support vision, audio & video
Tick the modalities your app needs — image, audio, video or PDF input, image or audio output — and instantly see which frontier models (GPT, Claude, Gemini, Llama, Qwen) actually support them, with each model's per-request media limits and a link to the provider doc. No signup, no API keys, sources cited.
How it works
This is a lookup-and-filter tool, not a calculator. Each of the 14model rows stores a set of boolean flags — does the documented API accept text, image, audio, video or PDF input, and does it produce image or audio output — copied verbatim from that provider's own API guide and cited per row. There is no arithmetic; the “methodology” is careful data compilation plus transparent filter logic.
- Modality flags.“Support” means the model's documented chat or generate API accepts or produces that modality — not a research demo and not a separate product. A provider's standalone text-to-speech endpoint, for instance, does not make its chat model “audio-out.” Unknown or unpublished support defaults to false, so a required-modality filter never over-promises.
- Hard limits. Where a doc publishes a numeric cap — images per request, image size, audio minutes, video minutes, context tokens — it is copied exactly with its unit. Where the provider publishes no fixed cap, the value is recorded as unknown and rendered
—, never a guessed number. - Filter logic. A model survives only if it supports every modality you tick (logical AND):
visible = models.filter(m => required.every(k => m[k] === true)). Provider and name filters narrow the set further. Everything runs client-side and instantly — no network calls, no keys. - Cross-check. Every filter is evaluated by two independent implementations (a
filterpass and areducepass) that must return the same model set, and all rows are validated to cite a source and carry no undefined limits. When both agree the card shows a “Cross-checked” badge — the same dual-method credibility idea used in our tax calculator.
The v1 list covers the major public-API models plus flagship open-weight models (Llama 4, Qwen2.5). Niche and long-tail models are deliberately omitted rather than implying exhaustive coverage. For token pricing, benchmark quality or free-tier quotas, see the related tools below — capability, cost and quality are three separate questions.
Worked examples
Frequently asked questions
Sources & references
- OpenAI — Images & vision guide (GPT-4o, GPT-4.1, o-series, GPT-5)
- OpenAI — Realtime API (GPT-4o audio in/out)
- Anthropic — Claude vision & document (image / PDF input, no audio or video)
- Google — Gemini video understanding (native long-video input)
- Google — Gemini audio understanding
- Meta — Llama 4 model cards (vision variants)
- Alibaba — Qwen model cards (Qwen2.5-VL / Qwen2.5-Omni)
Every model row above links its exact provider doc — expand a row to open it. Modality flags and limits were last cross-checked against these sources on 2026-07-03, and the list is reviewed whenever a major model ships.
Related tools
Comments & feedback
Spotted a bug or want an improvement? Tell us — our team reviews every comment, and good ideas get built. Comments are public and anonymous.
Spotted a model whose modality support has changed, or want one added?
Email me at [email protected] — I re-verify against the provider docs and update within a day.