Pick by use case
Best AI video model for text in video
This is the rare use case with an honest "none of them" answer. On-screen text rendering is a documented failure mode on every covered AI video model — letters garble, words mutate frame to frame, and anything past roughly six characters (four on Vidu) becomes illegible. The reliable workflow is to generate the footage without text and composite captions, logos, and labels in your editor. Below is how far each model garbles, so you know what to expect if you must generate text in-frame.
Deciding attribute: readable on-screen text — which no covered model produces reliably
Short answer
No AI video model renders readable on-screen text reliably — it is a documented failure across every covered model, garbling past roughly six characters (four on Vidu). Generate footage without text and add captions, logos, and labels in post.
Models ranked for on-screen text, captions & logos
1. Google Veo 3
SituationalVeo is the least-bad of the covered models for short in-frame text — a few-character word may hold more often than on peers — but it still garbles past roughly six characters. Treat any legible result as luck, not reliability, and keep a post-composite fallback ready.
Most relevant documented failure: Text Rendering Failure
2. Runway Gen-4
SituationalRunway garbles past roughly six characters like most of the field. Short signage (e.g. a four-letter word) is occasionally legible, but longer labels mutate across frames. Its real strength is everything around the text — character continuity — not the text itself.
Most relevant documented failure: Text Rendering Failure
3. OpenAI Sora 2
Avoid hereSora documents the same text-rendering failure (garbled past ~6 characters) and is sunsetting (consumer app closed 2026-04-26, API to September 2026), so it is no longer a practical pick for new text-in-video work regardless.
Most relevant documented failure: Text Rendering Failure
4. Vidu
Avoid hereVidu garbles text past roughly four characters — the earliest threshold of any covered model — so it is the worst pick for any in-frame text. Use it only for its reference-to-video character strength, never for signage or labels.
Most relevant documented failure: Text Rendering Failure
What to check before you commit credits
- →Plan for post — the reliable path is silent/text-free generation plus captions and logos composited in your editor.
- →Character count — most models garble past ~6 characters; Vidu past ~4. Even short words mutate frame to frame.
- →Frame-to-frame stability — text that looks right in one frame often warps in the next; check the whole clip, not a thumbnail.
- →Don't burn credits proving it — assume in-frame text fails and budget zero re-rolls for it.
FAQ
Which AI video model renders readable text?
None reliably. Text rendering is a documented failure on every covered model — all garble past roughly six characters, and Vidu past four. The dependable workflow is to generate footage without text and add captions, logos, and labels in post.
Why does text look garbled in AI-generated video?
Video models learn pixel patterns, not letterforms, so they approximate text instead of spelling it — and re-sample each frame, which makes words mutate over time. This text-rendering failure is documented across every covered model and worsens past a handful of characters.
How do I add text to an AI video correctly?
Generate the footage without any in-frame text, then composite captions, logos, prices, and labels in your video editor. This is the only reliable approach, since every covered model documents a text-rendering failure that garbles words past a few characters.
Can any AI video model spell a logo or sign correctly?
Not reliably. Short words occasionally render legibly — Veo is the least-bad — but anything past roughly six characters garbles on every covered model. Treat a correct result as luck and composite real text in post for anything brand-critical.
Go deeper
Consistency ranking
Which model is most consistent
All 9 models ranked by documented failure profile.
Head-to-head
Sora vs Veo — and where text fails on both
Dimension-by-dimension comparison.
Head-to-head
Vidu vs Runway — text legibility compared
Dimension-by-dimension comparison.
All use cases
Best model by use case
Talking-head, character, product, text.
Failure reference
Documented failure modes
Catalogued across every covered model.
Score before you generate
AVA scores your prompt against each model's documented failure profile
The free Chrome extension flags which documented failure your prompt is most likely to hit on each model — before you spend the credits. Pick by track record, not by demo reel.
Last updated: 2026-06-12. Grounded in AVA's documented per-model failure catalogue.