Machine Learning · head to head
Google Vertex AI vs Lambda Labs

Google Vertex AI
Machine Learning
Unified ML platform to build, deploy, and scale AI models
- From
- On request
- Rated
- -
The short version
- Each has a real cost: Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult; Lambda Labs on demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed
- They diverge on capability: Google Vertex AI covers AutoML, Lambda Labs covers NVIDIA GPUs.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Google Vertex AI and Lambda Labs actually diverge.
| Attribute | Google Vertex AI | Lambda Labs |
|---|---|---|
| Starting price | On request | $1.1/per-hour |
| Pricing model | Unknown | usage-based |
| Platforms | Cloud, Web | Cloud |
| Category | Machine Learning | AI |
| Founded | 2008 | 2012 |
Identical on both: free tier (No), 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 Google Vertex AI
- AutoML
- Custom training
- Feature Store
- Model monitoring
- Prediction serving
- BigQuery
- Cloud Storage
- TensorFlow
Only in Lambda Labs
- NVIDIA GPUs
- Pre-installed frameworks
- Persistent storage
- SSH access
- JupyterLab
- VSCode
- SSH
- Cloud support
What people use each for
The jobs each tool is most often brought in to do.
Google Vertex AI
- Machine learningnot Lambda Labs
- Data analysisnot Lambda Labs
- Model trainingnot Lambda Labs
- Predictive analyticsnot Lambda Labs
Lambda Labs
- Renting GPU instances for model training and inferencenot Google Vertex AI
- Short term access to high memory accelerators without buying hardwarenot Google Vertex AI
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Google Vertex AI
- Vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
- Requires familiarity with Google Cloud Platform infrastructure and concepts
- Cost can escalate quickly with large training and inference workloads
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
Pricing, plan by plan
Google Vertex AI
On requestNo published plan breakdown. See the Google Vertex AI review.
Lambda Labs
$1.1/per-hour- On-Demand$1.1/per-hour
- A10 GPU
- Instant availability
- ReservedFree
- Volume discounts
- Guaranteed capacity
Which should you pick?
Choose Google Vertex AI if
- You need automl.
- You work on Cloud, Web.
- You also want custom training.
Choose Lambda Labs if
- You need nvidia gpus.
- You work on Cloud.
- You also want pre-installed frameworks.
Questions people ask
- Is Google Vertex AI or Lambda Labs better?
- Neither clearly leads. Google Vertex AI starts at On request and Lambda Labs at $1.1/per-hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Google Vertex AI or Lambda Labs?
- Google Vertex AI starts at On request and Lambda Labs at $1.1/per-hour.
- Does Google Vertex AI or Lambda Labs run on more platforms?
- Google Vertex AI runs on Cloud, Web. Lambda Labs runs on Cloud.
- What is Google Vertex AI best used for?
- Google Vertex AI is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Lambda Labs is typically brought in for.
- What can Google Vertex AI do that Lambda Labs cannot?
- Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Lambda Labs covers NVIDIA GPUs, Pre-installed frameworks, Persistent storage, SSH access.
Answered from the vendors’ own pages
Google Vertex AI: What is the pricing model for Google Vertex AI?
Vertex AI uses a pay-as-you-go model with no upfront costs or lock-in fees. Costs vary by service: training is billed by compute resources and time (30-second increments), online predictions by machine type per hour, and batch predictions by compute time or per-record for specific AutoML types.
SourceLambda 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.
SourceGoogle Vertex AI: What types of data can Vertex AI handle?
Vertex AI supports image, video, text, and tabular data types with tools for uploading, storing, and managing large datasets.
SourceLambda 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).
SourceGoogle Vertex AI: Does Vertex AI support custom model training?
Yes. Vertex AI supports both AutoML for automated machine learning and custom training code in Python, R, and other languages.
SourceLambda 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.
SourceGoogle Vertex AI: What deployment options are available in Vertex AI?
Vertex AI supports online predictions for real-time use cases and batch predictions for large-scale processing.
SourceLambda 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.
SourceRelated pages
More on Google Vertex AI
More on Lambda Labs
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- Lambda Labs vs Databricks
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- Lambda Labs vs Comet ML
- Lambda Labs vs Dataiku
- Lambda Labs vs Domino Data Lab
- Lambda Labs vs DVC
- Lambda Labs vs Kubeflow
- Lambda Labs vs BentoML
- Lambda Labs vs Pachyderm
- Lambda Labs vs Apache Spark MLlib
- Lambda Labs vs Weaviate
- Lambda Labs vs Weights & Biases
- Lambda Labs vs Alteryx
- Lambda Labs vs Anaconda
- Lambda Labs vs Anthropic API
- Lambda Labs vs Fathom
- Lambda Labs vs Pika
- Lambda Labs vs D-ID
- Lambda Labs vs RunPod
- Lambda Labs vs CoreWeave
- Lambda Labs vs Modal
- Lambda Labs vs Banana
- Lambda Labs vs Replicate
- Lambda Labs vs Black Forest Labs
- Lambda Labs vs Jasper
- Lambda Labs vs AI21 Labs
- Lambda Labs vs Manus
- Lambda Labs vs NotebookLM
- Lambda Labs vs Poe
- Lambda Labs vs Poolside
- Lambda Labs vs QuillBot

