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Veo 3 character consistency: the image-to-video reference workflow in 2026
Character
consistency
Use one or two reference images in Veo 3.1 to keep the face, clothing, proportions, and framing more stable between shots.
Use reference images.
One or two frame images
for tighter shot control.
If you want a starting point, adapt one of the Veo 3 prompt examples.
Google's Vertex AI documentation says Veo can use subject images to preserve appearance, and that workflow supports up to three images of a single person, character, or product. Google's October 16, 2025 Veo 3.1 guide also points to reference images for keeping characters and styles consistent across multi-shot scenes.
On UlazAI today, one image URL centers the generation around a source frame, and two image URLs create a first-frame to last-frame transition. Test it in Studio, compare render prices, or use the API documentation.
Google supports subject images.
UlazAI uses one or two
frame images today.
Need the prompt side first? Go to Veo prompting best practices. Need account access before you buy? Start with the free-access guide.
- Reference images: use a clear image that shows the subject's face, shape, and key details.
- Generate: open Studio with one or two reference frames.
- Verify: Google documents a broader subject-image workflow than UlazAI currently exposes.
Reference images preserve appearance
Google's Vertex AI docs say Veo can use subject images to preserve the appearance of a person, character, or product in the output video. That is the real foundation behind character consistency in Veo.
Up to three subject images
The official reference-image workflow supports up to three images of a single person, character, or product. That is broader than a basic image-to-video prompt and closer to a consistency workflow.
One or two frame images today
Veo 3.1 accepts one or two imageUrls for frame control. Use one image to anchor the shot, or two images to define a first-frame to last-frame transition.
What to expect from character consistency right now
Reference images reduce visible drift, but they do not guarantee an identical character in every generation.
A workable character-consistency flow for UlazAI
Start from a strong source frame
Use one clear source image when the goal is to keep one character's face, styling, outfit, or silhouette stable. If the shot must transition between two controlled states, use a first frame and last frame.
Keep identity traits fixed in the prompt
Do not rewrite the character every time. Reuse the same age, clothing, hairstyle, accessories, camera distance, and tone anchors so the frame input and the text prompt are not fighting each other.
Test fast before you scale
Run the workflow in Veo 3.1 Fast first. When the identity and motion feel stable enough, then move into the paid path or the higher-quality route for production output.
imageUrls, and generation details.Prompt tips that keep a character consistent across clips
The reference image does half the work. These four prompt habits do the rest, and they matter most when you render clip two, three and four of the same character.
Do: repeat the identity block word for word
Write one sentence that names age, hair, outfit and one distinguishing detail, then paste it unchanged into every prompt. "A 7-year-old with curly red hair, yellow raincoat, one front tooth missing" must read exactly the same in each clip - paraphrasing it is the fastest way to drift.
Don't: restyle the character between shots
If clip one says "yellow raincoat" and clip two says "red jacket", the model follows the newer instruction. Change only the action, camera and location per clip, never the appearance words.
Do: anchor voice and demeanor alongside looks
Consistency is more than the face. Fix the voice description ("quiet, high-pitched, slightly hoarse") and one demeanor note ("cautious, observant") in the same block, so audio and body language stay recognisable too.
Don't: reuse a failed render as your reference
A frame that already drifted - softer jaw, different outfit - becomes the new baseline when you feed it back. Go back to the original source image or first frame when a shot misses, instead of chaining drift forward.
Google's reference-image workflow accepts up to three subject images of one person, character or product, which is documented in Google's official video docs. Pair that subject anchor with the habits above and check every generated shot against a saved still of clip one.
FAQ
Does Google Veo 3 support reference images for character consistency?
Yes. Google's Vertex AI documentation says Veo can use subject images to preserve appearance in generated video output.
How many reference images can the official workflow use?
Google's reference-image guide says the subject-image workflow supports up to three images of a single person, character, or product.
What does UlazAI support right now?
Veo 3.1 uses one image URL to anchor a shot or two image URLs to define the first and last frame of a transition.
Where can I test character consistency?
Open Veo 3.1 Studio, add one or two reference images, and compare the face, clothing, proportions, and framing in every generated shot.
How do I write prompts that keep a character consistent across clips?
Write one identity sentence - age, hair, outfit, one distinguishing detail - and paste it unchanged into every prompt. Change only action, camera and location per shot, keep voice and demeanor descriptions fixed, and go back to the original source image when a render drifts instead of chaining the drifted frame forward.
Test character consistency in Studio
Try one or two reference images in Studio. Compare packages before a paid render, or read the docs for the image URL parameters.
Official references: Google Vertex AI reference-image guide and Google's October 16, 2025 Veo 3.1 prompting guide.
Keep a character recognisable across separate video shots
Use the same clean reference images for face, hair, clothing and distinctive accessories. A reference can anchor appearance, but it cannot rescue prompts that change age, wardrobe or lighting from shot to shot.
Plan each shot with one action and repeat the fixed character details. Test two adjoining shots first; if the hand-off fails, shorten the scene or simplify the movement before building a longer sequence.