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Poe vs Amazon Redshift ML

Poe logo

Poe

AI

Chat platform that gives access to many AI models from one subscription

From
Free
Free plan
Yes
Visit PoeFull review
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
Visit Amazon Redshift MLFull review

The short version

  • Free plans on both; paid from $4.99/mo and $0.25/mo.
  • Only Poe lists custom bots; only Amazon Redshift ML lists local inference.
  • Where Poe falls short: points-based pricing makes cost per message hard to predict across models.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

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

Attributes where Poe and Amazon Redshift ML differ
AttributePoeAmazon Redshift ML
Pricing modelFreemiumUsage-based
PlatformsWeb, iOS, Android, Windows, macOSWeb
CategoryAIMachine Learning
Founded20092006

Identical on both: starting price (Free), free tier (Yes).

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 Poe

  • Multi-model chat
  • Custom bots
  • Image and video generation
  • Points-based usage
  • API access for bot creators

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.

Poe

  • Comparing responses across multiple AI modelsnot Amazon Redshift ML
  • Building and sharing custom prompt-based botsnot Amazon Redshift ML
  • Accessing premium models without separate subscriptionsnot Amazon Redshift ML
  • Generating images or video from a chat interfacenot 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 Poe
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Poe
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Poe
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Poe

Where each one falls short

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

Poe

  • Points-based pricing makes cost per message hard to predict across models
  • Heavy usage of top-tier models can exhaust points quickly on lower plans
  • No native fine-tuning or persistent long-term memory across bots
  • Custom bots are limited to prompt engineering rather than full agent tooling

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

Poe

Free
  • FreeFree
    • Limited daily messages across select models
  • Starter$4.99/mo
    • Monthly compute points
    • Access to premium models
  • Premium$19.99/mo
    • Larger monthly point allowance
    • Priority access to premium models
  • Premium Plus$49.99/mo
    • Higher point allowance for heavy usage

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 Poe if

  • You need multi-model chat.
  • You want to start without paying.
  • You work on Web, iOS, Android, Windows, macOS.
  • You also want custom bots.
Poe 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 Poe or Amazon Redshift ML better?
Neither clearly leads. Poe 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, Poe or Amazon Redshift ML?
Poe starts at Free and Amazon Redshift ML at Free.
Does Poe or Amazon Redshift ML run on more platforms?
Poe runs on Web, iOS, Android, Windows, macOS. Amazon Redshift ML runs on Web.
Can I use Poe for free?
Both have a free tier, so you can try either at no cost before committing.
What is Poe best used for?
Poe is most often used for comparing responses across multiple ai models, building and sharing custom prompt-based bots, accessing premium models without separate subscriptions, generating images or video from a chat interface. Of those, comparing responses across multiple ai models and building and sharing custom prompt-based bots are not what Amazon Redshift ML is typically brought in for.
What can Poe do that Amazon Redshift ML cannot?
Poe covers Multi-model chat, Custom bots, Image and video generation, Points-based usage. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

Poe: How does Poe's pricing work?

Poe uses a monthly points system: each subscription tier grants a pool of compute points that are spent per message, with the amount depending on which underlying AI model is used.

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.

Poe: Is there a free plan on Poe?

Yes, Poe offers a free tier with limited daily messages across a selection of models before users need a paid subscription for more access.

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.

Poe: What do the paid subscription tiers cost?

Poe offers Starter at $4.99/month, Premium at $19.99/month, and Premium Plus at $49.99/month, each granting a larger monthly pool of compute points.

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.

Poe: What happens if I run out of points?

Once a subscription's monthly point allowance is exhausted, further use of premium models is limited until the points refresh or the user upgrades or purchases more.

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.

Poe: Can developers build on Poe?

Yes, Poe lets creators build and publish custom bots, and developers can connect their own model endpoints as bots via Poe's API.

Source
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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