TabPFN-3.5

TabPFN-3.5

Prior Labs
TimesFM-3

TimesFM-3

Google
+
+

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About

TabPFN-3.5 is a tabular foundation model built for state-of-the-art predictions on structured data. It supports a wide range of prediction tasks, including churn, fraud, pricing, demand forecasting, risk, and other real-world data science problems, allowing teams to serve multiple use cases with one model. The model works with data as it is, handling missing values, outliers, categorical features, multi-table datasets, free text as a feature, thousands of distinct IDs without encoding, and hundreds of measurements per row. Users can feed in raw data, skip feature engineering and preprocessing, and get production-grade predictions from the first predict call. TabPFN-3.5 performs predictions in a single forward pass and is designed for both accuracy and speed, with fast inference for latency-critical predictive workflows. It supports production-scale datasets of up to one million rows natively and delivers 20x faster inference than previous model versions.

About

TimesFM-3 is a state-of-the-art time series foundation model designed for highly accurate multivariate forecasting in a single forward pass. The 330 million parameter model is pre-trained on a real-world and synthetic time-series corpus comprising more than 1 trillion time points, building on the efficiency and zero-shot generalization of earlier TimesFM models. It can jointly predict multiple coevolving time series and capture dependencies that improve accuracy without task-specific fine-tuning. The model supports multiple targets with point and quantile forecasts, past covariates that are known only historically, and past-future dynamic covariates such as planned promotions, holidays, or weather forecasts. TimesFM-3 uses a decoder-only transformer architecture, processes contiguous data in patches of 32 time steps, and applies alternating causal temporal attention and full variate attention to combine patterns across time and related series.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Data scientists, machine learning teams, and organizations needing to build fast, production-ready predictions from structured data

Audience

Data scientists, researchers, and developers wanting to forecast multiple related time series and incorporate historical and known future signals

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Prior Labs
Founded: 2024
Germany
priorlabs.ai/tabpfn-3-5

Company Information

Google
Founded: 1998
United States
research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/

Alternatives

TabFM

TabFM

Google

Alternatives

CodeQwen

CodeQwen

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MiMo-V2-Flash

MiMo-V2-Flash

Xiaomi Technology
Kimi K2

Kimi K2

Moonshot AI
TimesFM-3

TimesFM-3

Google
Qwen-7B

Qwen-7B

Alibaba
Seed2.0 Pro

Seed2.0 Pro

ByteDance

Categories

Categories

Integrations

Amazon Web Services (AWS)
Databricks
Google Cloud Platform
Microsoft Azure
Model Context Protocol (MCP)
NVIDIA DRIVE
Python
SAP Cloud Platform
Snowflake

Integrations

Amazon Web Services (AWS)
Databricks
Google Cloud Platform
Microsoft Azure
Model Context Protocol (MCP)
NVIDIA DRIVE
Python
SAP Cloud Platform
Snowflake
Claim TabPFN-3.5 and update features and information
Claim TabPFN-3.5 and update features and information
Claim TimesFM-3 and update features and information
Claim TimesFM-3 and update features and information