Palantir AIP supports a wide range of LLMs (large language models) and text embedding models from leading providers, including xAI, OpenAI, Anthropic, Meta, and Google. Supported models are listed on this page and can be used across the Palantir platform to power AIP workflows, though availability may differ across enrollments (for instance, due to georestriction).
Learn how to configure the selection of LLMs available for use on your enrollment..
The following LLMs are supported for use with AIP, subject to enrollment availability.
Palantir AIP also supports the following text embedding models:
AIP is model-agnostic and supports a diverse selection of models for LLM-powered use cases; for more information, refer to this list of all models available in AIP.
However, LLM selection and availability differs across enrollments based on certain prerequisites for a specific model to be available on an enrollment. The criteria are listed below:
For information on LLM rate limits, review the documentation on LLM capacity management.
Some enrollments may have access to a limited set of models because of geographical restriction (or georestriction for short); georestriction for a certain region means that any AIP request to a LLM stays within the boundaries of that region. For example, if an enrollment is defined as EU geo-restricted, all LLM requests will be processed in the EU. Non-georestricted enrollments have access to the full set of Palantir-supported models.
The following table indicates the regional georestriction options for the various models supported by AIP. Note that the regional georestriction refers to the enrollment setup, not to the location of a specific user.
Model Provider | Model | US | EU | UK | CA | AU | JP |
---|---|---|---|---|---|---|---|
xAI | Grok-3-beta | ✅ | |||||
xAI | Grok-3-mini-beta | ✅ | |||||
Bedrock | Claude 4 Sonnet | ✅ | ✅ | ||||
Bedrock | Claude 3.7 Sonnet | ✅ | ✅ | ||||
Bedrock | Claude3.5 Haiku | ✅ | |||||
Vertex | Gemini 1.5 Pro | ✅ | ✅ | ✅ | |||
Vertex | Gemini 2.0 Flash | ✅ | ✅ | ||||
Azure / OpenAI | GPT-4.1 | ✅ | ✅ | ||||
Azure / OpenAI | GPT-4.1-mini | ✅ | |||||
Azure / OpenAI | GPT-4.1-nano | ✅ | ✅ | ||||
Azure / OpenAI | ada002 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Azure / OpenAI | embedding3-large | ✅ | ✅ | ✅ | |||
Azure / OpenAI | embedding3-small | ✅ | ✅ | ✅ | ✅ | ||
Azure | o4-mini | ✅ | |||||
Azure | o3 | ||||||
Azure / OpenAI | o1-mini | ✅ | ✅ | ||||
Azure / OpenAI | o1-preview | ✅ | ✅ | ||||
xAI | Grok-2 | ✅ | |||||
xAI | Grok-2-vision | ✅ | |||||
Bedrock | Claude 4 Opus | ✅ | ✅ | ||||
Bedrock | Claude3.5 Sonnet v2 | ✅ | ✅ | ✅ | |||
Bedrock | Claude3.5 Sonnet | ✅ | ✅ | ||||
Bedrock | Claude3 Sonnet | ✅ | ✅ | ✅ | ✅ | ✅ | |
Bedrock | Claude3 Haiku | ✅ | ✅ | ✅ | ✅ | ||
Vertex | Gemini 1.5 Flash | ✅ | ✅ | ✅ | |||
Azure / OpenAI | GPT-4o | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Azure / OpenAI | GPT-4o-mini | ✅ | ✅ | ||||
Azure | o3-mini | ✅ | ✅ | ||||
Azure / OpenAI | o1-mini | ✅ | ✅ | ||||
Azure / OpenAI | o1-preview | ✅ | ✅ | ||||
Azure | GPT4 (8K, 32K) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Azure | GPT3.5 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Open source (Palantir-hosted) | Llama3 8B | ✅ | ✅ | ✅ | ✅ | ✅ | |
Open source (Palantir-hosted) | Llama3 70B | ✅ | ✅ | ✅ | ✅ | ✅ | |
Open source (Palantir-hosted) | Llama3.1 8B | ✅ | ✅ | ✅ | ✅ | ✅ | |
Open source (Palantir-hosted) | Llama3.1 70B | ✅ | ✅ | ✅ | ✅ | ✅ | |
Open source (Palantir-hosted) | Llama3.3 70B | ✅ | ✅ | ✅ | ✅ | ✅ | |
Open source (Palantir-hosted) | Mixtral 8x7B | ✅ | ✅ | ✅ | ✅ | ✅ | |
Open source (Palantir-hosted) | Document Information Extraction | ✅ | ✅ | ✅ | ✅ | ✅ |
Bring your own model is a capability that provides first-class support for customers that would like to connect their own LLMs or accounts to use in AIP with all Palantir developer products - AIP Logic, Pipeline Builder, Agent Studio, Workshop, etc.
Review the bring your own model documentation to learn how to register models for use in AIP.
Note: AIP feature availability is subject to change and may differ between customers.
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