Agent model choice

Available models

Warp lets you choose from a curated set of Large Language Models (LLMs) to power your Agentic Development Environment.

Warp supports the following models.

The model_id values shown below can be used when configuring models via the Oz Platform or CLI.

Auto models

Model	model_id	Description
Auto (Responsive)	auto	Selects the highest-quality, fastest available model. May consume credits more quickly.
Auto (Cost-efficient)	auto-efficient	Optimizes for lower credit consumption while maintaining strong output quality.
Auto (Genius)	auto-genius	Adapts to task complexity and selects Warp’s most capable model when it’s worth it. Best for deep debugging, architecture decisions, and /plan sessions.
Auto (Open-weights)	auto-open	Routes between the best open-source models available in Warp. Optimizes for low cost and fast speed using open-weights models.

All Auto models perform well across all agent workflows and are ideal if you prefer Warp to manage model selection dynamically.

OpenAI

Model	model_id	Reasoning Level
GPT-5.5	gpt-5-5-low	Low
GPT-5.5	gpt-5-5-medium	Medium
GPT-5.5	gpt-5-5-high	High
GPT-5.5	gpt-5-5-xhigh	Extra High
GPT-5.4	gpt-5-4-low	Low
GPT-5.4	gpt-5-4-medium	Medium
GPT-5.4	gpt-5-4-high	High
GPT-5.4	gpt-5-4-xhigh	Extra High
GPT-5.3 Codex	gpt-5-3-codex-low	Low
GPT-5.3 Codex	gpt-5-3-codex-medium	Medium
GPT-5.3 Codex	gpt-5-3-codex-high	High
GPT-5.3 Codex	gpt-5-3-codex-xhigh	Extra High
GPT-5.2 Codex	gpt-5-2-codex-low	Low
GPT-5.2 Codex	gpt-5-2-codex-medium	Medium
GPT-5.2 Codex	gpt-5-2-codex-high	High
GPT-5.2 Codex	gpt-5-2-codex-xhigh	Extra High
GPT-5.2	gpt-5-2-low	Low
GPT-5.2	gpt-5-2-medium	Medium
GPT-5.2	gpt-5-2-high	High
GPT-5.2	gpt-5-2-xhigh	Extra High

Anthropic

Model	model_id	Variant
Claude Opus 4.7	claude-4-7-opus-xhigh	Default effort
Claude Opus 4.7	claude-4-7-opus-high	High effort
Claude Opus 4.7	claude-4-7-opus-max	Max effort
Claude Opus 4.6	claude-4-6-opus-high	Default effort
Claude Opus 4.6	claude-4-6-opus-max	Max effort
Claude Sonnet 4.6	claude-4-6-sonnet-high	Default effort
Claude Sonnet 4.6	claude-4-6-sonnet-max	Max effort
Claude Opus 4.5	claude-4-5-opus	Thinking off
Claude Opus 4.5	claude-4-5-opus-thinking	Thinking on
Claude Sonnet 4.5	claude-4-5-sonnet	Thinking off
Claude Sonnet 4.5	claude-4-5-sonnet-thinking	Thinking on
Claude Haiku 4.5	claude-4-5-haiku	—

Google

Model	model_id
Gemini 3.1 Pro	gemini-3.1-pro

Hosted models (via Fireworks AI)

Warp also supports leading open source models hosted via Fireworks AI, so you can run them from inside Warp without setting up your own inference infrastructure.

Model	model_id
GLM 5	glm-5-fireworks
GLM 5.1	glm-5.1-fireworks
Kimi K2.5	kimi-k25-fireworks
Kimi K2.6	kimi-k26-fireworks
Minimax 2.7	minimax-2.7-fireworks
Qwen 3.6 Plus	qwen-3.6-plus-fireworks

How to change models

You can use the model picker in your prompt input to quickly switch between models. The currently active model appears directly in the input editor.

Model selector in Warp’s input.

To change models, click the displayed model name (for example, Claude Sonnet 4.5) to open a dropdown with all supported options. Your selection will automatically persist for future prompts.

Model fallback

Warp uses a model fallback system to ensure uninterrupted service if your selected model becomes temporarily unavailable due to provider outages or capacity issues.

How it works:

• If your selected model isn’t available, Warp automatically uses a fallback model from a predefined chain to continue your conversation without errors.
• As soon as your originally selected model becomes available again, Warp automatically switches back to it.
• The fallback model is selected to provide comparable quality and capabilities to your original choice.

Configuring models per Agent Profile

You can configure the base model for each Agent Profile, alongside the Agent’s autonomy, tool access, and other permissions. The base model is also used for Planning.

Edit your default profile or any other profile directly in Settings > Agents > Profiles.

Zero data retention policies

Warp integrates with multiple Large Language Model (LLM) providers to power its AI-driven features.

These providers include, but are not limited to:

• OpenAI
• Anthropic
• Google
• xAI
• Fireworks AI

Warp has executed Zero Data Retention (ZDR) agreements with these providers. This means that, by default across all plans:

• LLM providers commit not to train their models on any customer-generated data processed through Warp’s services.
• LLM providers commit to delete inputs and outputs after generating the relevant output, within a fixed time period.

Warp enforces these commitments through both technical measures and contractual safeguards with the LLM providers.