# Weights & Biases alternatives: what AI models name instead, November 2026

Gane Index, November 2026 Edition. 239 of the 252 answers in the 1 category where Weights & Biases holds a standing named it neither first nor as an alternative; these are the first choices those answers made. Page: https://www.gane.ai/index/it/vendors/weights-biases/alternatives

## Named instead, most often (every category and segment added)

- Databricks Mosaic AI: 37
- Azure Machine Learning: 34
- Google Vertex AI: 21
- Amazon SageMaker: 20
- Google Colab: 9
- Dataiku: 8

## ML platforms

**Small business**: 76 of 84 answers did not name Weights & Biases (Weights & Biases is #10 of 15 at 2%).

- Google Vertex AI: first choice in 16 of those 76
- Google Colab: first choice in 5 of those 76
- Azure Machine Learning: first choice in 4 of those 76
- MLflow: first choice in 4 of those 76
- Amazon SageMaker: first choice in 3 of those 76
- Hugging Face: first choice in 3 of those 76
- KNIME Analytics Platform: first choice in 3 of those 76
- DataRobot: first choice in 2 of those 76

**Mid-market**: 80 of 84 answers did not name Weights & Biases (Weights & Biases is #13 of 15 at 0%).

- Azure Machine Learning: first choice in 12 of those 80
- Databricks Mosaic AI: first choice in 10 of those 80
- Amazon SageMaker: first choice in 7 of those 80
- Dataiku: first choice in 5 of those 80
- Google Colab: first choice in 4 of those 80
- MLflow: first choice in 4 of those 80
- KNIME Analytics Platform: first choice in 3 of those 80
- PyTorch: first choice in 2 of those 80

**Enterprise**: 83 of 84 answers did not name Weights & Biases.

- Databricks Mosaic AI: first choice in 27 of those 83
- Azure Machine Learning: first choice in 18 of those 83
- Amazon SageMaker: first choice in 10 of those 83
- Google Vertex AI: first choice in 5 of those 83
- Dataiku: first choice in 3 of those 83
- Domino Data Lab: first choice in 2 of those 83
- Amazon Bedrock: first choice in 1 of those 83
- Azure AI: first choice in 1 of those 83

Published under CC BY 4.0. The output is the models' output; nothing here is a recommendation by the index.