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AI · head to head

Leonardo AI vs Amazon Redshift ML

Leonardo AI logo

Leonardo AI

AI

AI-powered creative suite for image generation

From
Free
Free plan
Yes
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning

SQL statements in Redshift that train models on SageMaker and return them as functions

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Leonardo AI video generation trails specialized video tools like Pika, with no native timeline editing or motion interpolation; Amazon Redshift ML training is billed by SageMaker separately from Redshift, so a feature that looks like a free SQL statement produces a second line item on a different part of the bill that the analyst who ran it usually cannot see.
  • They diverge on capability: Leonardo AI covers Text-to-image, Amazon Redshift ML covers CREATE MODEL in SQL.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Leonardo AI and Amazon Redshift ML actually diverge.

Attributes where Leonardo AI and Amazon Redshift ML differ
AttributeLeonardo AIAmazon Redshift ML
Pricing modelUnknownusage-based
PlatformsWeb, APIWeb
CategoryAIMachine Learning
Founded20222006

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Leonardo AI

  • Text-to-image
  • Model training
  • Canvas editor
  • Motion generation
  • API access
  • Photoshop plugin
  • Web support
  • Api support

Only in Amazon Redshift ML

  • CREATE MODEL in SQL
  • Automatic model selection
  • Local inference
  • Bring your own model
  • Algorithm selection
  • Cost ceiling controls
  • Existing warehouse security
  • Batch and interactive scoring

What people use each for

The jobs each tool is most often brought in to do.

Leonardo AI

  • ai tools managementnot Amazon Redshift ML
  • Workflow automationnot Amazon Redshift ML
  • Reportingnot Amazon Redshift ML

Amazon Redshift ML

  • Adding a churn or propensity score to an existing dashboard where the data is already in Redshift and nobody needs a bespoke modelnot Leonardo AI
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Leonardo AI
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Leonardo AI
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Leonardo AI

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Leonardo AI

  • Video generation trails specialized video tools like Pika, with no native timeline editing or motion interpolation
  • Credits consume rapidly for professional use, particularly at 4K resolution
  • Limited traditional image editing tools compared to desktop software
  • Image quality and consistency inconsistent compared to some competitors on certain prompt types
  • Advanced features requiring custom model training add complexity and cost

Amazon Redshift ML

  • Training is billed by SageMaker separately from Redshift, so a feature that looks like a free SQL statement produces a second line item on a different part of the bill that the analyst who ran it usually cannot see.
  • Autopilot searches many candidate models by default and the duration and cost of CREATE MODEL scale with the data size and the MAX_CELLS setting, so an unconstrained statement against a large table is an expensive accident rather than an experiment.
  • Local inference runs on the Redshift cluster itself, so scoring millions of rows competes for the resources the warehouse exists to provide, and the remote inference alternative adds a per-batch network call plus an hourly SageMaker endpoint charge that persists whether or not anyone queries it.
  • The supported problem types are limited to what the exposed algorithms cover, so anything involving text, images, sequences, a custom loss function or a bespoke evaluation metric is out of scope and has to be built conventionally.
  • There is no retraining schedule, drift detection or model registry, so a model created by a statement stays exactly as trained until somebody remembers to recreate it, and nothing in the warehouse will report that its accuracy has decayed.

Pricing, plan by plan

Leonardo AI

Free
  • Essential$12/month
    • 8,500 monthly tokens
    • Fine-tuned models
    • Image-to-image
  • Premium$30/month
    • Unlimited relaxed generation on Phoenix and Lucid Origin models
    • Faster generation speed
    • Advanced options
  • Ultimate$60/month
    • 60,000 monthly tokens
    • Maximum concurrent jobs
    • Highest priority generation queue

Amazon Redshift ML

Free
  • Free TrialFree
    • 2-month trial
    • 750 DC2.Large hours
  • On-Demand$0.25/hour
    • Per-node pricing
    • SageMaker training

Which should you pick?

Choose Leonardo AI if

  • You need text-to-image.
  • You want to start without paying.
  • You work on Web, API.
  • You also want model training.
Leonardo AI review

Choose Amazon Redshift ML if

  • You need create model in sql.
  • You want to start without paying.
  • You also want automatic model selection.
Amazon Redshift ML review

Questions people ask

Is Leonardo AI or Amazon Redshift ML better?
Neither clearly leads. Leonardo AI starts at Free and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Leonardo AI or Amazon Redshift ML?
Leonardo AI starts at Free and Amazon Redshift ML at Free.
Does Leonardo AI or Amazon Redshift ML run on more platforms?
Leonardo AI runs on Web, API. Amazon Redshift ML runs on Web.
Can I use Leonardo AI for free?
Both have a free tier, so you can try either at no cost before committing.
What is Leonardo AI best used for?
Leonardo AI is most often used for ai tools management, workflow automation, reporting. Of those, ai tools management and workflow automation are not what Amazon Redshift ML is typically brought in for.
What can Leonardo AI do that Amazon Redshift ML cannot?
Leonardo AI covers Text-to-image, Model training, Canvas editor, Motion generation. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

Leonardo AI: Does Leonardo AI grant commercial rights to generated images?

Yes. All Leonardo AI plans grant full ownership and unrestricted commercial rights to generated images, allowing creators to sell AI-generated art and use outputs in commercial products.

Source
Amazon Redshift ML: Does it require SageMaker?

Yes. Redshift ML is an interface; the training happens in SageMaker and needs an IAM role and an S3 bucket for the intermediate data.

Leonardo AI: How does Leonardo's Real-Time Canvas work?

The Real-Time Canvas is a freeform workspace where images generate as you draw, type prompts, or add elements, updating the output approximately every 2 seconds per stroke, supporting inpainting, outpainting, and composite editing.

Source
Amazon Redshift ML: Is there an extra charge?

The SQL interface is part of Redshift, but the training runs as a SageMaker job charged at SageMaker rates, and a remote inference endpoint is billed for as long as it exists.

Leonardo AI: What models does Leonardo AI offer beyond its own?

Leonardo API supports both in-house models (Phoenix, Lucid Origin, Lucid Realism) and third-party models including FLUX.1, Ideogram 3.0, GPT Image, Kling, Veo, and others under a unified pay-as-you-go API surface.

Source
Amazon Redshift ML: What kinds of model can it build?

Regression, binary and multiclass classification through the automatic path, plus direct use of XGBoost, linear learner, multilayer perceptron and K-means. Anything beyond structured tabular prediction is out of scope.

Leonardo AI: What is included in the free tier?

The free plan provides 150 tokens per day enabling hundreds of images per month, but outputs are non-commercial only; paid plans starting at $12/month unlock commercial rights and higher token allocations.

Source
Amazon Redshift ML: Can I use a model I trained myself?

Yes, through the bring-your-own-model path, either compiled into the cluster for local inference or called as a remote SageMaker endpoint.

Amazon Redshift ML: Does it retrain automatically?

No. Retraining means running CREATE MODEL again, on a schedule you build yourself, and nothing in the product monitors whether it is needed.

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