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AI · head to head

Lambda Labs vs Amazon Redshift ML

Lambda Labs logo

Lambda Labs

AI

GPU cloud for deep learning

From
$1.1/per-hour
Free plan
No
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

  • Only Amazon Redshift ML has a free tier, so it costs nothing to try first.
  • Each has a real cost: Lambda Labs on demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed; 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: Lambda Labs covers NVIDIA GPUs, 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 Lambda Labs and Amazon Redshift ML actually diverge.

Attributes where Lambda Labs and Amazon Redshift ML differ
AttributeLambda LabsAmazon Redshift ML
Starting price$1.1/per-hourFree
Free tierNoYes
PlatformsCloudWeb
CategoryAIMachine Learning
Founded20122006

Identical on both: pricing model (usage-based), 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 Lambda Labs

  • NVIDIA GPUs
  • Pre-installed frameworks
  • Persistent storage
  • SSH access
  • JupyterLab
  • VSCode
  • SSH
  • Cloud 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.

Lambda Labs

  • Renting GPU instances for model training and inferencenot Amazon Redshift ML
  • Short term access to high memory accelerators without buying hardwarenot 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 Lambda Labs
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Lambda Labs
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Lambda Labs
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Lambda Labs

Where each one falls short

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

Lambda Labs

  • On demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed
  • H100 pricing varies within a band, at $3.99 to $4.29 an hour per GPU, so the rate is not fixed
  • Reserved capacity is arranged by contacting the team rather than self serve
  • Prices are quoted before applicable tax

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

Lambda Labs

$1.1/per-hour
  • On-Demand$1.1/per-hour
    • A10 GPU
    • Instant availability
  • ReservedFree
    • Volume discounts
    • Guaranteed capacity

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 Lambda Labs if

  • You need nvidia gpus.
  • You work on Cloud.
  • You also want pre-installed frameworks.
Lambda 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 Lambda Labs or Amazon Redshift ML better?
Neither clearly leads. Lambda Labs starts at $1.1/per-hour and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Lambda Labs or Amazon Redshift ML?
Amazon Redshift ML has a free tier; the other does not. Paid plans start at $1.1/per-hour for Lambda Labs and Free for Amazon Redshift ML.
Does Lambda Labs or Amazon Redshift ML run on more platforms?
Lambda Labs runs on Cloud. Amazon Redshift ML runs on Web.
Can I use Amazon Redshift ML for free?
Yes. Amazon Redshift ML has a free tier, so you can try it without paying. Lambda Labs starts at $1.1/per-hour.
What is Lambda Labs best used for?
Lambda Labs is most often used for renting gpu instances for model training and inference, short term access to high memory accelerators without buying hardware. Of those, renting gpu instances for model training and inference and short term access to high memory accelerators without buying hardware are not what Amazon Redshift ML is typically brought in for.
What can Lambda Labs do that Amazon Redshift ML cannot?
Lambda Labs covers NVIDIA GPUs, Pre-installed frameworks, Persistent storage, SSH access. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

Lambda Labs: What does Lambda Labs GPU pricing depend on?

Lambda Labs pricing depends on the GPU model (H100, B200, A100, V100, etc.), cluster size, and contract length. For example, a 16-GPU H100 cluster costs $6.16/GPU/hour for 2 weeks to 1 year, while A100 GPUs are $1.99-$2.79/GPU/hour.

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.

Lambda Labs: Are there volume discounts for larger GPU clusters?

Yes. Pricing decreases with larger cluster orders. For example, NVIDIA H100 clusters cost $6.16/GPU/hour for 16 GPUs, $5.85/GPU/hour for 64 GPUs, and $5.54/GPU/hour for 256 GPUs (all for 2 weeks to 1 year terms).

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.

Lambda Labs: Can I get custom pricing for a long-term GPU contract?

Yes. For cluster orders of 16+ GPUs with 1-year or longer contracts, Lambda Labs offers custom pricing. Contact their sales team to request a quote.

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.

Lambda Labs: What additional costs should I expect beyond the hourly GPU rate?

All listed prices are plus applicable sales tax, VAT, or GST depending on your location.

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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