Hailuo vs Kling 3: Which One Actually Finishes the Shot

I ran both of these for a month on the same brief — short vertical clips for social, product in frame, one person moving. I expected the comparison to come down to which one rendered better. It didn't. It came down to aspect ratio, which is a deeply boring answer that saved me about two weeks.

So let me put the conclusion at the top, then explain it, because if you're making vertical video the decision is already made and you can stop reading.

The short version

Hailuo is the better physics engine. Kling is the better production tool. Hailuo renders how materials actually behave — water tension, the difference between how silk and cotton fall, hair carrying inertia when the wind hits it. That's genuinely ahead of the field and you can see it in a single clip.

But Hailuo outputs 16:9 and has no native audio. Kling does vertical natively, ships synchronised audio on the right tier, and will extend a clip well past the ten-second native ceiling. For anything going to TikTok, Reels or Shorts, that isn't a tiebreaker — it's the whole decision, and no amount of superior cloth simulation gets you out of cropping a horizontal frame into a vertical one.

Where Hailuo genuinely wins

Physical plausibility, and it isn't close. If your shot involves liquid, fabric, hair, smoke, or anything settling under its own weight, Hailuo handles it with a realism the others approximate. A dress moving as someone turns is the test I use, because it's the one most models fail in an obvious way — the fabric floats or snaps back wrong, and it reads as fake instantly.

That matters more than it sounds. Most of what makes AI video look like AI video isn't resolution, it's physics that your eye rejects before you can articulate why. I wrote about that failure mode in why AI videos look fake, and Hailuo fixes more of it than anything else at this price.

It's also cheap. Around $9.99/month gets you a couple of minutes of 1080p, which works out to a few dollars per finished minute — and per-clip it can undercut Kling significantly on silent output.

Where Kling wins

Everything about actually shipping a video.

• Native vertical. 9:16 out of the box, not cropped. If you've ever tried to salvage a 16:9 render for Reels you know why this sits at the top of the list — see aspect ratio for why cropping loses the shot.
• Audio in the same render. On the tiers that include it, you skip a whole second generation step and the sync problems that come with it.
• Extend. Native clips are around ten seconds like everyone else's, but Kling will chain them out toward three minutes. Whether the result holds together is a separate question, but the capability is there.
• Camera control. Tracking shots and multi-shot sequences behave closer to what you asked for. If you work with motion references at all, this is the one that cooperates — more on that in motion control.

Entry pricing starts lower too, around $6.99/month, with a free tier of daily credits that expire in 24 hours. Full breakdowns in Kling 3 pricing and Hailuo pricing.

Side by side

Figures here reflect published plans at time of writing and move often — check the current pages before committing. A month-long hands-on comparison with similar findings is worth reading at goenhance.

The honest limits of this comparison

Two things I can't tell you from a month of use.

First, this is a snapshot of two moving targets. Both models ship revisions on a timescale of weeks, and a physics advantage is exactly the kind of thing that gets closed by a point release. Anything you read here — including the vertical-output gap, which is a product decision rather than a hard limit — could be obsolete by the time you act on it.

Second, my brief was narrow. Short vertical product clips with one person in frame is not the same test as narrative filmmaking, and I'd expect the ranking to move if you're cutting a three-minute sequence where Kling's extend feature and multi-shot handling carry far more weight than they did for me.

So which one

Pick Kling if you're making social video, if you need audio, if your output is vertical, or if you want one tool that gets you from prompt to publishable. That covers most people reading this.

Pick Hailuo if realism is the product — fabric, liquid, hair, anything where a physics artefact kills the shot — and you're fine finishing in an editor. It's also the better choice when budget is the binding constraint and you don't need audio baked in.

And if you're weighing either against the rest of the field, the neighbouring comparisons are Veo 3 vs Kling 3 and Seedance vs Kling. If you're going to run either through an API rather than the web app, the per-second economics are in AI video API pricing.

Frequently asked questions

Is Hailuo better than Kling?
At simulating physical materials, yes. At producing a finished social video, no — Kling's vertical output, native audio and extend feature win on practical grounds for most projects.

Can Hailuo make vertical videos?
Not natively. It outputs 16:9, so vertical means cropping, which costs you framing on a shot that was composed horizontally.

Which is cheaper?
Kling starts lower on subscription and has a free daily-credit tier. Hailuo can be cheaper per silent clip. Once you add a separate audio pass to Hailuo the gap narrows or reverses.

How long can clips be?
Both generate around ten seconds natively. Kling extends beyond that by chaining segments, toward roughly three minutes.

Do I need both?
Rarely. The cost of running two models is retries while you relearn each one's prompt behaviour. Pick the one that matches your output format and get fluent in it.

Where to take this next

The comparison that matters isn't the one in a blog post — it's the one you run on your own brief, with your own product in frame. That's usually three or four test prompts and an afternoon, and it settles the question permanently.

Looking for something else? Browse all 140 AI video guides in one list.

Join the AI Video Generator community on Skool — we post the test prompts and the raw renders, so you can see which model failed where instead of taking my word for it.