
{/* banner prompt: A playful, polished 3D clay-render in matte sage green, cream and terracotta: a stylized NVIDIA RTX 3060 graphics card, and a cute rounded clay whale with a faint glowing cyan wireframe pattern on its side, swimming above a row of three small rounded screens each showing a tiny version of the same whale, tiny clapperboard and soft concentric sound-wave props, soft studio shadows, simple pale cream background, gentle depth of field, warm muted palette, no text, no people, 16:9. */}

Our homepage has an electric whale — a glowing cyan wireframe humpback swimming through a digital ocean — playing behind the headline. It was made for a wide desktop screen, so on a phone it gets cropped to a sliver. We wanted a proper **portrait** version for mobile, and it turned into a small experiment worth writing down: take *one* keyframe and hand it to three different video models — one running locally on our RTX 3060, and two frontier models in the cloud — then judge them honestly.

The twist, as usual, is that "cheapest," "best-looking," and "the one we actually shipped" were three different answers.

## The setup: one keyframe, three animators

Everything starts from a single still. We generated a 9:16 keyframe on the same RTX 3060 that runs the rest of this series — a cyan low-poly wireframe whale over a glowing data grid, with a magenta flare and purple depth to match the original. Then that identical image went, unchanged, into each of the three models as the first frame. Same whale, same starting composition — only the motion model changes.

That is the fair way to compare image-to-video: hold the input constant and watch what each model *does* with it.

## MiniMax H3 — local, free, and it actually works

First, the home team. [MiniMax H3](/blog/2026/08/04-now-it-talks-open-source-video-with-sound-on-the-same-rtx-3060/) is an open-weights model we already run locally, streaming its 50-odd GB of weights through a 12GB card a slice at a time.

<YouTube id="xaG_naHmBPg" />

The result is genuinely good: the whale swims with a real, gentle tail undulation and the model even grows its own drifting data-particles by the end. It is coherent, on-style, and it cost nothing but electricity and patience — **about 20 minutes for a 3-second clip at 512×896**. That is the honest local trade-off: free and completely private, but slow, shorter, and lower-resolution than the cloud. As a proof that a consumer card can do this at all, it's a quiet triumph.

## Veo 3.1 — the calm, cinematic one

Next, Google's Veo 3.1 Fast, through the Gemini API, from the exact same keyframe.

<YouTube id="k-lnccxtRPM" />

This is where the jump in production value shows. In **under a minute** and for **a dollar or two**, Veo returned a smooth **720×1280, 8-second** clip — and, unprompted, built an entire digital ocean around the whale: a rippling grid, parallax depth, drifting stars. The motion is calm and ambient, which matters when the video lives *behind* a headline. It never fights the text. This is the one we shipped.

## Sora 2 — the most beautiful, and the one on a clock

Finally, OpenAI's Sora 2, same keyframe again.

<YouTube id="00272-n56_Q" />

On pure craft, Sora 2 makes the best whale of the three. The wireframe mesh is the most refined, and the motion is the most lifelike — a graceful full-body dive with fins and flukes that move like they have weight. It was also the cheapest of the cloud runs (~$0.80 for 8 seconds) and quick (~2 minutes).

There are two catches. First, that gorgeous, dramatic motion is *busier* — stunning as a hero, harder to sit quietly behind text. Second, and decisively for us: **OpenAI's Sora 2 video API stops accepting requests on 24 September 2026.** Building a banner on an API that disappears next week is not a plan.

## A quick colour lesson

One thing the experiment taught us: image models have opinions. Our first keyframes came out pure cyan on black — the model kept stripping the magenta flare and purple wash that give the original its identity. No amount of prompting fixed it; the model simply preferred cyan. The fix was to stop arguing and **composite the magenta back in** — a flare and a purple gradient added to the keyframe in a few lines of code. Every model then faithfully carried that palette through the animation. Sometimes the right move is to give the model a picture, not an argument.

## The verdict

| | Where | Best at | The catch |
|---|---|---|---|
| **MiniMax H3** | Local, RTX 3060 | Free, private, no API | Slow, short, lower-res |
| **Veo 3.1** | Google, cloud | Calm, cinematic, ambient | Paid per second |
| **Sora 2** | OpenAI, cloud | Most beautiful, most lifelike | API shuts down 24 Sep 2026 |

If you want free and private, the local model already does it. If you want the most beautiful single clip, Sora 2 wins — for just a few more days. But for a banner that has to loop quietly behind a headline *and* still be regenerable next month, **Veo 3.1 was the right tool** — and it's the whale now swimming on our homepage when you open [tyolab.com](https://www.tyolab.com) on your phone.

The best-looking model and the right one are rarely the same tool. We keep relearning that, one whale at a time.


79fe4348d5fa7fd1a4e55fd884ded88badb8423f1b073f29c27be5c89a948967

A hands-on comparison of MiniMax H3 (local, RTX 3060), Google Veo 3.1 and OpenAI Sora 2 for image-to-video — from one shared keyframe — judged on motion, fidelity, speed, cost and which API will still exist next week.

We wanted a portrait version of the electric whale on our homepage, so we animated the same AI-generated keyframe with a local model on our RTX 3060 and two frontier cloud models. Free-and-private, best-and-sustainable, and best-looking turned out to be three different answers.

Tag: Veo

Tag: Veo

One Whale, Three Video Models: MiniMax H3 vs Veo 3.1 vs Sora 2