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Each AI provider is a function you assign as a computed column on a TableModel. Create the table with pxt schema update. In notebooks you can still call add_computed_column(). Each provider page lists its API key and optional extras. If a provider is missing, wrap it in a @pxt.udf or ask on GitHub Discussions.

Cloud LLM providers

Anthropic Claude

Claude models for language and multimodal generation

Google Gemini

Gemini via Google AI Studio or Vertex AI

OpenAI

GPT models for text, embeddings, and image analysis

Azure OpenAI

OpenAI models via Azure

Mistral AI

Mistral language models

DeepSeek

DeepSeek language and code models

Groq

Groq-hosted models

Model hubs

Platforms that host or route many models from a shared catalog.

Hugging Face Hub

CLIP, DETR, sentence-transformers, ViT, Speech2Text, and more

Replicate

Run models on Replicate

Together AI

Open-source models via Together

Fireworks

Fireworks inference

OpenRouter

One API across many LLM providers

AWS Bedrock

Models through Bedrock

Nebius

Nebius Token Factory via an OpenAI-compatible API

Embeddings and reranking

Voyage AI

Embeddings and reranking for text, images, and video

Jina AI

Embeddings and reranking for search

Twelve Labs

Multimodal embeddings via the TwelveLabs Embed API

Media generation

BFL (FLUX)

FLUX image generation and editing from Black Forest Labs

fal.ai

Flux, Stable Diffusion, and other image models

RunwayML

Runway video generation

Local LLM runtimes

Llama.cpp

Local LLMs on CPU and GPU

Ollama

Local open-source models via Ollama

vLLM

High-throughput local inference

Computer vision

YOLOX

Object detection with YOLOX

Voxel51

Image and video datasets with FiftyOne

Audio

Whisper / WhisperX

Speech recognition with Whisper

Enterprise

Microsoft Fabric

Azure OpenAI through Microsoft Fabric

DataFrames

Pandas

Import and export pandas DataFrames. Do not use pandas as the database that holds your app data.
Provider notebooks: docs/release/howto/providers.
Last modified on September 3, 2026