Image to Video AI: Complete 2026 Guide (Every Model and Workflow)

Image to video AI turns a still image into a short video clip by predicting motion from the picture and a short prompt; in 2026 the main models are Kling, Google's Veo 3.1, ByteDance's Seedance 2.0, the open-source Wan 2.2, Runway and Hailuo. Which one fits depends on three things: what kind of image you start from, what you can spend, and whether a face has to stay the same across clips.

Checked October 2026 against Kling's Element Library guide and credit guide, Google's Veo 3.1 Gemini API docs and Flow credits page, ByteDance Seed's Seedance 2.0 launch post, the Wan 2.2 repository, Runway pricing, Hailuo's payment policy and OpenAI's Sora discontinuation notice. Video prices change almost monthly.

If your goal is an AI influencer or any recurring character, read this alongside our AI influencer video guide, which ranks the same tools by how well they hold one persona's face. This page is the broader model-and-workflow view: every input type, every budget, and the steps that make the output usable.

How image to video AI works

You give the model a start image and a motion prompt. The model keeps what it can see in the frame and invents everything else: the back of a head, the other side of a product, what the room looks like when the camera moves. That is why the same model can be excellent on a product turntable and poor on a person turning around. The more the clip has to invent, the more it drifts.

Models handle this in three ways. Single-frame models animate one start image. First-and-last-frame models interpolate between two images you supply. Reference models take several images of a subject (or a short clip) and keep that subject consistent while they generate a new scene. For anything with a recurring face, reference models win.

Best image to video AI in 2026: the models compared

These are the models worth knowing in October 2026, with how they take identity information and what they cost to start. Prices are list prices, checked October 2026.

Kling

Kling's Element Library stores a reusable subject: at least 2 and up to 4 reference images with a front-facing main image recommended, or a 3 to 8 second video of the character that also captures the voice. In VIDEO 3.0 Omni you call the element with "@" in the prompt. Kling 4.0 began an early rollout on September 28, 2026; our Kling 4.0 tracker follows it. Standard is $8.80 a month for 660 credits after a first-month discount, and the free tier's output is not licensed for commercial use. Settings are in our Kling image-to-video tutorial, and the free Kling AI credit calculator turns a weekly clip count into a plan.

Veo 3.1 and Google Flow

Google's Veo 3.1 docs list three image inputs: a start frame, a start plus last frame for interpolation, and up to 3 reference images of a person, character or product. Durations are 4, 6 or 8 seconds, and 8 seconds is required with reference images or 1080p and 4K. In the Flow app everyone gets 50 credits a day, and Google AI Plus at $4.99 a month adds 200 monthly credits; a 720p Gemini Omni Flash clip costs 7 to 15 credits for 4 to 10 seconds (Flow credits, checked October 2026). Audio is generated with the video.

Seedance 2.0

ByteDance's Seedance 2.0 is a multimodal audio-video model first released in China in February 2026. Its launch post says it can take up to 9 images, 3 video clips and 3 audio clips with a text instruction, and pull composition, motion, camera movement and sound from them; the model's paper lists 4 to 15 second outputs at 480p and 720p. It is the strongest option when one scene needs several characters or props. Two cautions from ByteDance itself: using real human portraits as references requires identity verification or legal authorisation, and multi-subject consistency still has room to improve. Consumer access is through Dreamina.

Wan 2.2 (open source)

The Wan 2.2 repository ships several models under Apache 2.0. TI2V-5B handles text and image to video at 720p and 24 fps, and its documented command runs on a 24 GB GPU such as an RTX 4090 with offloading. I2V-A14B is the larger image-to-video model at 480p and 720p, with a single-GPU example that assumes 80 GB. Wan2.2-Animate takes a character image plus a driving video and transfers the motion. ComfyUI has an official Wan 2.2 workflow tutorial; if you have not installed ComfyUI yet, start with our ComfyUI install guide. For the Animate model, follow the Wan 2.2 Animate tutorial.

Runway and Hailuo

Both animate a single start image well and suit B-roll and product shots. Runway's pricing page lists a free plan with 125 one-time credits and Standard at $15 a month for 625 credits, with Gen-4.5 at 12 credits a second, so a 5-second clip uses 60 credits. Hailuo's payment policy lists Standard at $14.99 for 1,000 credits, though a newer Hailuo post cites a lower price, so check at checkout. Checked October 2026. Our Runway Gen 4 guide covers References and credits, and the MiniMax H3 guide covers running Hailuo's model in ComfyUI.

Which image to video AI should you use? The selection guide

Start from what you actually have. The input decides the model more than any quality ranking does.

For general video quality rather than identity, our best AI video generators ranking scores the same field differently.

Image to video AI free: what you can do without paying

• Google Flow: 50 credits a day for everyone, enough for a few short 720p clips with audio.
• Runway: 125 one-time credits, about two 5-second Gen-4.5 clips.
• Kling: a free tier whose output is not licensed for commercial use, so do not post sponsored content made on it.
• Wan 2.2: free and open source, limited only by your GPU and time.

No hosted service we checked offers unlimited free generation. Our free AI video generators guide lists every free allowance and its commercial-use terms.

The image to video workflow that produces usable clips

Most identity problems start in the stills. If the face drifts on a side angle in images, it drifts worse in motion. Our consistent character AI guide covers locking a face with reference models, ID adapters or a face LoRA before you animate anything.

The AI Influencers course teaches this pipeline on one persona end to end: locked stills, subject references, motion prompts, voice and the edit, with the ComfyUI workflows for the local route.

Image to video AI generator settings by photo type

The same model behaves differently depending on what is in the frame. These are the patterns that hold across the tools above.

Portraits and characters

Faces are the hardest case because viewers notice small changes. Keep the head angle within what the image shows, ask for small motions (a blink, a smile, a slight turn, hair moving) and let the camera do the rest. When the character must appear in many clips, build a subject from two to four angles in Kling or Veo 3.1 rather than reusing one start frame. If the source photo is of a real person, you need their permission: ByteDance requires verification or authorisation for real portraits in Seedance 2.0, and every major platform restricts realistic AI likenesses of people who did not consent.

Product photos

Products animate well when the camera moves and the product stays still: a slow orbit, a push in, light sweeping across the surface. Hands picking up a product are where models still invent extra fingers or warp labels. Veo 3.1 accepts a product as a reference image, which helps keep the packaging consistent across shots; for single shots, Runway and Hailuo are reliable.

Landscapes, interiors and old photos

Wide scenes tolerate invention better than faces, so even single-frame models do well with drifting clouds, water, a camera dolly through a room or a parallax move across an old photo. Keep the prompt to the camera move and the one element that should move. Restoring and upscaling an old photo before animating it gives the model more to work with than the original scan.

Making videos longer than one clip

Every model here produces short clips, so longer videos are edits. Three techniques do most of the work:

• Last frame to first frame. Export the final frame of a clip and use it as the start image of the next. Veo 3.1's first-and-last-frame mode lets you also set where the next clip ends.
• Shot lists, not long takes. Plan a sequence of 4 to 8 second shots with cuts between them, the way an editor would. Cuts hide small changes in the face or background that a continuous take exposes.
• Consistent references across shots. Reuse the same Kling element or Veo reference images for every shot so the character and props stay the same.

Budget for retakes. If you keep one take in three, your real cost per finished second is three times the list price, which is why testing at short length on a cheap plan comes before upgrading.

Common image to video mistakes

• Re-describing the image in the prompt. "A woman in a red coat in Tokyo at night" fights the picture; "walks forward, wind in her hair" works with it.
• Asking for a big turn from one frame. A single front-facing image tells the model nothing about the profile. Use references or keep the head angle small.
• Long clips on the first try. Drift grows with length. Find the motion at 4 to 6 seconds, then extend.
• Judging a model on one take. Output varies from take to take; compare three or four per model before switching.
• Skipping the label. Meta requires its AI disclosure on photorealistic video, and TikTok and YouTube have equivalent rules; our Instagram AI label guide shows where the setting is.

Image to video AI: FAQ