TabFM Models by Google
1 model2026
Last refreshed 2026-07-01. Next refresh: weekly.
Details
ResearcherGoogle
LicenseNoncommercial
Commercial useCommercial use: non-commercial
Models1
Released2026
About
TabFM is Google's tabular foundation model for zero-shot classification and regression on structured tables. It frames tabular prediction as an in-context learning problem, using training examples and target rows as a unified prompt so users can generate predictions in a single forward pass without per-dataset model training, hyperparameter tuning, or manual feature engineering. Google Research released TabFM with public GitHub code and downloadable pretrained weights on Hugging Face, and says BigQuery integration via AI.PREDICT is planned.
Decision facts
- Best fit
- tabularcodingstructured outputs
- Capability starting point
- TabFM 1.0.0
- Lowest tracked input
- Not tracked
- Closest related family
- Google Cloud Text-to-Speech
Current Variants
Use-when guidance is based on each model's tracked capabilities, context window, release date, and replacement status.
1 in view
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| TabFM 1.0.0 | Use when the workload needs tabular. | 2026-06 | tabular | Current |
Release Timeline
1 release group2026-06
1 current
TabFM 1.0.0
Currenttabular
Specifications(1 models)
| Model | Released |
|---|---|
| TabFM 1.0.0 | 2026-06 |