First look at Venice AI video generation: models, prompts, and credits

What Venice video generation offers and how privacy works

Venice video generation lives in the model menu, where you will find separate tabs for image to video and text to video. Some models produce audio along with the video, others do not. Open-source options include the Wan 2 family and Ovi, which is based on Wan. These are uncensored, so they are the ones to reach for if you want unfiltered output. The menu also lists corporate models: Kling 2.5, Google's Veo 3.1, and OpenAI's Sora 2.

Privacy follows the same architecture as the rest of Venice. Your prompt and chat are never stored on a server; they live only in your browser. Individual generations are either anonymized or fully private. Anonymized means the request is not private but your identity is shielded from the model provider. You can read model-by-model details on the Venice blog.

Once you pick a model and adjust your settings, Venice shows the credit cost of that generation before you run it.

Testing open-source models: Wan 2.5 and Ovi

The Wan 2.5 preview is an audio model used here in image-to-video mode and set to anonymized. The workflow: drag in a source image, write a prompt describing the camera movement and scene, then adjust resolution and duration in settings. The example used an anime-style image of a painter with this prompt:

Camera circles around the skilled painter to showcase a breathtaking lush
landscape of majestic mountains and serene rivers alongside the imposing
ancient castle.

At 1080p and 10 seconds with AI enhancement on, this generation cost 110 credits and took 220 seconds. The result had a cinematic parallax effect and on-theme music. After any generation you can copy the last frame and continue it to keep a shot going.

Ovi is the speed-and-cost contrast. The same kind of image-to-video task ran for 22 credits and finished in 41 seconds, while still pulling extra detail into the scene. Ovi has fewer settings beyond variant count, but it is the cheaper, faster open-source option.

Two pro tips for higher-quality results

The first tip is to generate your image first. Create an image with one of Venice's image models, pick the one you like, and click the create video button. This switches you to an image-to-video model with your chosen image already loaded, so you control the starting frame.

The second tip is to write the video prompt with a Venice chat model before you generate. Save your image, upload it to a new chat using Venice Large so its vision can see the picture, and ask it to write the prompt for you. For example:

I want to animate this image, so help me generate a detailed prompt for a
video generation. I want the double doors to close as the camera dollies
forward. Create a 1 to two paragraph prompt.

Paste that detailed prompt back into the create-video flow. In the demo, running this through Veo 3.1 at full quality (8 seconds, 16x9) cost 352 credits and produced a smooth, detailed result. Expect to iterate; you will not always nail it on the first try.

Comparing Kling 2.5 Turbo Pro and Veo 3.1

These models respond well to filmmaking terminology, so detailed, technical prompts pay off. The example used a text-to-video shot with shallow depth of field, golden-hour lighting, and explicit camera and film-stock notes:

Extreme close-up dolly shot of a mortar grinding lapis lazuli into ink,
shallow depth of field emphasizing textured hands and stone grain. Sunlight
creeps across a Florentine workshop workbench over 10 seconds during golden
hour, revealing scattered dried herbs and parchment pigment recipes.
Chiaroscuro lighting transitions to candle-lit close-up of the artisan's
weathered face as dusk falls. Practical candle flicker illuminating linen
sleeves, 24mm anamorphic lens, 24 frames per second, Kodak Vision3 500T
film grain.

Kling 2.5 Turbo Pro at 10 seconds cost 77 credits. The same scene was run side by side on Veo 3.1 Fast, where the top duration is 8 seconds; since Kling has no audio, audio was enabled on Veo. The speed gap was large: Veo 3.1 Fast finished in 105 seconds, Kling took 293 seconds. Veo applied the requested film grain and lighting transition closely, while Kling delivered a strikingly realistic, weathered human face even though it skipped the candle flicker. Each model has different strengths, so it is worth comparing.

Sora 2 Pro and extending videos with the last frame

Sora 2 Pro handles complex, multi-shot scenes. A detailed text-to-video prompt describing a tracking shot, high-angle wide shot, and time-lapse produced not a single shot but a full scene. In settings you can push duration up to 12 seconds and resolution to 1080p, each of which raises the credit cost (for example, the demo's prompt rose from 264 to 396 credits at 12 seconds, and to 444 at 1080p). A 9:16 vertical version was generated with the same prompt.

To extend a clip, click copy the last frame and continue, which keeps you in image-to-video mode using that frame as the new starting image. To keep the style consistent, copy your previous prompt into a fresh chat (Venice Small works) and ask it to write a continuation:

Help me generate a new video generation prompt to continue this scene in
the same Renaissance era style.

Paste the new prompt, confirm your aspect ratio and resolution, and generate. The extended shot picked up the same characters, focus shifts, and even dialogue cues from the prompt, lining up with the original to form a continuous series.

How the credit system works and where to go next

Your Venice account shows credits based on your DIEM (DM) balance, your USD balance, and any Venice credits you have purchased. One US dollar equals 100 Venice credits, and one DM is worth 100 Venice credits per day. Before every generation, the interface displays exactly how many credits the current prompt and settings will use.

Open-source models cost fewer credits than the corporate closed-source models, with Sora 2 being the most expensive. Checking the credit estimate before you run a job lets you balance cost against quality and speed. Once you start generating, Venice invites you to share your projects in the Venice AI Discord.

Key takeaways

• Venice video generation runs from text or images, keeps prompts in your browser, and offers each generation as anonymized or fully private.
• Open-source models like Wan and Ovi are uncensored, cheaper, and faster; corporate models like Kling, Veo, and Sora cost more and excel at different things.
• Quality improves when you generate a starting image first and use a Venice chat model with vision to write a detailed, film-literate prompt.
• The last-frame feature plus a continuation prompt lets you extend clips into a consistent multi-shot series, while the credit estimate shows the cost before you commit.