Image and video decision

Krea

You can self-host core image-generation features because Krea publishes an open-source repo, but the hosted product's value relies on proprietary models and inference infrastructure that are costly and hard to match; build for experimentation or narrow workflows, keep paying for full production scale and enterprise capabilities.

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You pay

$9/mo

$108/yr

Read off the official pricing page.

You’d pay instead

$20one-off6 h to build

$2,000/mo10 h/mo upkeep

On cash alone, building overtakes the subscription at 223 seats.

What a replacement has to do

  • Provide a web UI to submit text+image prompts, run the open-source Krea model to generate images, store and serve results, and an endpoint for upscaling/LoRA fine-tuning.

What it still won’t have

  • Krea-hosted inference infrastructure and latency/scale optimizations
  • Automatic model updates and access to their proprietary/commercial models and model catalog
  • Enterprise features (SLA, audit logs, user seats, hosted compute packages)
  • Convenience of integrated web app, workflow automation nodes, and managed LoRA training

What remains hard

  • Proprietary modelsPowerful proprietary models
  • Proprietary modelsKrea 2 is our first foundation image model built completely from scratch, focused on aesthetic diversity, style control, and expressive visual direction.
  • Infrastructure at scaleWe put a lot of effort into having one of the strongest inference infrastructures to make models like Flux or Krea-1 to work in just seconds.
  • Infrastructure at scaleIndustry-leading inference speed
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 223 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

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What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a self-hosted instance of Krea 2 using the official krea-2 GitHub repo on a single GPU VM. Stack: Ubuntu 22.04, Docker, Docker Compose, Postgres, MinIO (S3-compatible), Nginx, and PyTorch/TensorRT. In scope: clone https://github.com/krea-ai/krea-2, wire environment variables, install model weights, run the model server container on a GPU (NVIDIA drivers + Docker runtime), deploy the backend API, run the web frontend, configure persistence (Postgres + MinIO), implement job queuing, and expose a simple prompt+upload UI. Out of scope: reimplementing model architecture or building multi-region autoscaling. Deliverables must include automated start scripts (docker-compose or k8s manifests), basic unit/integration tests for API endpoints, error handling for model failures and OOMs, and documentation of GPU instance type and monthly cost assumptions.
How we checked4 sources · 1/1 runs agreed · evidence score 99

How the score was reached

  • Self-host verdict base92
  • An open-source build was found+5
  • 4 cited sources+3
  • Price verified on pricing page+3
  • 1/1 assessment runs agreed+4
  • Hard moats found in the evidence-6
  • Evidence score99

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 4

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 1 independent runs, one answer✓ Citations limited to fetched pages! 4 moats quoted from the page