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AI · head to head

AI21 Labs vs Amazon Redshift ML

AI21 Labs logo

AI21 Labs

AI

Enterprise language AI solutions

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: AI21 Labs the free allowance is $10 of credit lasting 7 days rather than an ongoing free tier; 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: AI21 Labs covers Jamba models, 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 AI21 Labs and Amazon Redshift ML actually diverge.

Attributes where AI21 Labs and Amazon Redshift ML differ
AttributeAI21 LabsAmazon Redshift ML
PlatformsApi, CloudWeb
CategoryAIMachine Learning
Founded20172006

Identical on both: starting price (Free), pricing model (usage-based), 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 AI21 Labs

  • Jamba models
  • Long context
  • RAG engine
  • Writing tools
  • REST API
  • Amazon Bedrock
  • Cloud platforms
  • 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.

AI21 Labs

  • Running long-context tasks on the Jamba model familynot Amazon Redshift ML
  • Building and optimising production AI agents with Maestronot Amazon Redshift ML
  • Routing between models to control cost and accuracynot Amazon Redshift ML
  • Long-horizon agentic tasks needing stateful workspacesnot 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 AI21 Labs
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot AI21 Labs
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot AI21 Labs
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot AI21 Labs

Where each one falls short

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

AI21 Labs

  • The free allowance is $10 of credit lasting 7 days rather than an ongoing free tier
  • Jamba Large is $2 per million input tokens and $8 per million output, so output-heavy work costs four times as much as input
  • Volume discounts, private cloud hosting and higher rate limits require a custom plan
  • Standard rate limits are not published

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

AI21 Labs

Free
  • Free TrialFree
    • 10 USD credits
    • 7-day trial period
    • No credit card required
  • Pay As You Go$undefined/mo
    • Usage-based pricing model
    • Access to all Foundation model APIs and SDK
    • Unlimited seats
  • Custom Plan$undefined/mo
    • Volume discounts on token pricing
    • Premium API rate limits
    • Private cloud hosting option

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 AI21 Labs if

  • You need jamba models.
  • You want to start without paying.
  • You work on Api, Cloud.
  • You also want long context.
AI21 Labs 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 AI21 Labs or Amazon Redshift ML better?
Neither clearly leads. AI21 Labs 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, AI21 Labs or Amazon Redshift ML?
AI21 Labs starts at Free and Amazon Redshift ML at Free.
Does AI21 Labs or Amazon Redshift ML run on more platforms?
AI21 Labs runs on Api, Cloud. Amazon Redshift ML runs on Web.
Can I use AI21 Labs for free?
Both have a free tier, so you can try either at no cost before committing.
What is AI21 Labs best used for?
AI21 Labs is most often used for running long-context tasks on the jamba model family, building and optimising production ai agents with maestro, routing between models to control cost and accuracy, long-horizon agentic tasks needing stateful workspaces. Of those, running long-context tasks on the jamba model family and building and optimising production ai agents with maestro are not what Amazon Redshift ML is typically brought in for.
What can AI21 Labs do that Amazon Redshift ML cannot?
AI21 Labs covers Jamba models, Long context, RAG engine, Writing tools. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

AI21 Labs: How much do AI21's Jamba Mini and Jamba Large models cost?

Jamba Mini costs $0.2 per 1M input tokens and $0.4 per 1M output tokens. Jamba Large is priced at $2 per 1M input tokens and $8 per 1M output tokens. Both models use usage-based billing with no monthly minimums.

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.

AI21 Labs: Does AI21 offer a free trial?

Yes, AI21 provides a free trial with 10 USD in credits for 7 days, no credit card required. The trial grants access to all Foundation models via API and SDK.

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.

AI21 Labs: How do AI21's custom plans and volume discounts work?

Custom plans with volume discounts are available for enterprises but require contacting sales. These plans can include premium API rate limits, private cloud hosting, priority support, dedicated account managers, and expert consultancy.

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.

AI21 Labs: What does AI21 mean by 30% token efficiency savings?

AI21 claims their tokenization delivers approximately 30% more text per token compared to other providers, which can reduce effective costs by roughly 30%. This applies primarily to English-language text averaging 1 word or 6 characters per token.

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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