r/HiggsfieldAI

From the mind of alexander kiesel, this is the masterpiece, now real talk, can hollywood make stuff like that?

Trying to turn generated fragments into something that feels edited, cinematic and intentional. Curious what you think 👀

https://www.youtube.com/watch?v=jM5R9phTCN4

Original pop-videos/Suno songs and more here.

FLUX / NO SEADANCE 2.0

I mean really… if someone like me, Alexander Kiesel, can suddenly build cinematic projects like this with a small studio setup, AI-assisted workflows, and enough obsession, then Hollywood is probably facing a much bigger shift than most people realize.

A few years ago this level of visual experimentation required massive teams, studio pipelines, insane budgets, and access almost nobody had.

This is a spec campaign I built for VELOUR which is a mock streetwear brand I created to develop my portfolio.
No brief from a client yet. Just a creative direction I set myself: rooftop, night, tonal dressing, zero noise. The goal was to see how close I could get to a real fashion film using only AI tools.
Stack used: Seedance 2.0 for the video, cinematic prompt engineering for the shot structure and grade direction.
This is the lane I'm building in, a cinematic AI creative direction for fashion and beauty brands. Not UGC, not talking heads. Editorial-grade output that a brand could actually run.
Portfolio: nandyvisuals.com/mediakit
Open to feedback from anyone who works with brands on the creative side on what reads as premium to a buyer and what doesn't?

Let me know your feedback!!

Made in nodes, but honestly saying outside of Comfy.

Used Seedance 2.0

Hey everyone,

If you use Higgsfield AI for cinematic video/image generation, you already know the pain: the platform hosts 30+ models (Kling, Sora 2, Veo, Seedance, Wan, Hailuo, DoP, Soul, Nano Banana, Seedream, Flux, GPT Image…) and each one has its own quirks, named presets, and aspect-ratio rules. 

While working on our own projects and writing prompts, we wanted an easier and more consistent way to do it so I built one.

GitHub: https://github.com/OSideMedia/higgsfield-ai-prompt-skill

License: MIT

Its for Claude Co work or Claude Code and it does the prompt-construction work and turns your creative brief into a production-ready Higgsfield prompt using the MCSLA formula (Model · Camera · Subject · Look · Action), with the right model selected, named camera/motion presets verified against the platform, shared negative constraints appended, and aspect-ratio enums respected.

It isn't: another MCP wrapper. Higgsfield already ships official execution tooling. this is the  prompt layer that sits in front of it.

The split is intentional:

You can paste prompts straight into higgsfield.ai if you want. Or you can wire it up to any of Higgsfield's official MCP/CLI Tools

This skill → produces the prompt → Higgsfield's stack → executes it

Check it out and let me know what you think 😄

zero prompt adherence, mashing together reference shots at random, ps3 look. wtf?

Using mainly higgsfield I made a whole sci fi movie after work in 2 months.

https://www.youtube.com/watch?v=-lxKKTfzwns

Hi everyone,

I’m looking into generating a large amount of video content and I’m trying to understand the real cost difference between using Higgsfield and using Kling directly.

Here’s my rough calculation:

Higgsfield:

Annual plan: $1,430/year
Credits: 26,000 credits/month
Total yearly credits: 312,000 credits
If Kling generation costs around 6 credits per second, then:
312,000 / 6 = 52,000 seconds of video per year
$1,430 / 52,000 = about $0.0275 per second

Kling direct:

Package: $3,780 for 30,000 credits
Generation cost: roughly 1 credit per second
So:
30,000 seconds of video
$3,780 / 30,000 = about $0.126 per second

Based on this, Higgsfield looks around 4.5x cheaper than using Kling directly.

But I’m not fully confident in this calculation. Am I understanding the Higgsfield credit system correctly? Is it really 6 credits per second for Kling, or is it 6 credits per clip/generation? Are there any hidden limitations, quality differences, concurrency limits, commercial usage restrictions, failed generation costs, or other caveats I should know about?

tldr: for high-volume video generation, is Higgsfield cheaper than using Kling directly, or is there a catch?

Hi everyone. I decided to share my non-commercial project I worked on a few months ago, focusing on the story behind the Toyota Hilux. It’s sort of a fun “pseudo-advertisement.” It’s a hybrid project using animation, RS Render, and AI. What do you think about this work?

Am I understanding this wrong