Hyperscaler ML platform
Google Vertex AI alternatives
What are the alternatives to Google Vertex AI?
The realistic field is 2 other hyperscaler ml platforms plus the adjacent categories below. Which one fits depends on why you are leaving — cost, portability, evaluation discipline and operational envelope pull in different directions, and no single alternative wins on all four.
Why teams leave
- You needed the trained weights to be portable and Gemini tuning is not
- Regional pricing variation made forecasting difficult
- You wanted a smaller product surface for a single workflow
Before you move: what Google Vertex AI is good at
If your data is already in BigQuery, the distance from data to trained model is shorter here than anywhere else, and that distance is usually where projects actually die.
Stay if
- Your data already lives in Google Cloud
- You want to tune Gemini rather than an open-weight model
- Procurement confines you to GCP
What a migration actually involves
- 01
Export training data from BigQuery as JSONL.
- 02
Retrain against an open-weight base — Gemini tunes cannot be moved.
- 03
Weigh the data-gravity cost honestly if you retrain frequently.
Direct alternatives
Same category, so the closest substitutes.
AWS SageMaker
The full machine-learning platform on AWS. Enormously capable, correspondingly heavy, and priced per instance-hour.
Onrup
Cost authorised before compute is leased, a blocking evaluation gate before deploy, and weights you can always download or publish. Head to head with Google Vertex AI.
Adjacent options
Different category, but frequently the right answer depending on why you are leaving.
Together AI
Managed fine-tuning platformA broad model API with fine-tuning attached, covering the widest catalogue of open-weight models of anyone in this set.
Fireworks AI
Managed fine-tuning platformInference, fine-tuning and evaluation behind one API, with fine-tuned adapters served at the same per-token rate as the base model.
Modal
Serverless GPU platformServerless compute for arbitrary Python, billed by the second. Not a fine-tuning product — a substrate you build one on.
Baseten
Serverless GPU platformModel deployment and serving with strong operational tooling, compliance posture and cold-start engineering.
Frequently asked questions
Why do teams leave Google Vertex AI?
You needed the trained weights to be portable and Gemini tuning is not; Regional pricing variation made forecasting difficult; You wanted a smaller product surface for a single workflow.
What do I lose by moving away from Google Vertex AI?
If your data is already in BigQuery, the distance from data to trained model is shorter here than anywhere else, and that distance is usually where projects actually die.
Can I export my model from Google Vertex AI?
Open-weight tunes export; Gemini tunes do not.
Can I tune Gemini here?
No. The catalogue is open-weight models only, which is the same reason everything trained here is downloadable.
Last verified 6 August 2026.
Start with the free tier
A magic link creates your account, your tenant and your first API key. No card until you ask for compute.