LLM ReferenceLLM Reference

o3 Deep Research

o3-deep-research

Researched 1d ago
ProprietaryMultimodalRAGAgentsLong contextVisionJSON / Tool use

o3 Deep Research has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Decision context: RAG task fit, 0 tracked provider routes, and research from 2026-05-14.

Use it for

  • Teams evaluating rag, agents, and long context
  • Workloads that can use a 200K context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Teams that need a tracked hosted API route today

Cheapest output

-

No tracked output price

Provider routes

0

No provider route in seed

Quality / dollar

Unknown

No task benchmark coverage yet

Freshness

2026-05-14

Researched 1d ago

fresh

Top use-case fit

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

About

o3-deep-research is OpenAI's advanced model for deep research, designed to tackle complex multi-step research tasks by synthesizing information from multiple sources at 200K context.

o3 Deep Research has a 200K-token context window.

Capabilities

VisionMultimodalReasoningFunction CallingTool UseStructured OutputsCode ExecutionPrompt CachingBatch APIAudioFine-tuning

Rankings

Specifications

Familyo3
Released2025-10-10
Context200K
ArchitectureDecoder Only
Specializationgeneral
LicenseProprietary
Trainingpretrained

Created by

Cutting-edge research and development.

San Francisco, California, United States
Founded 2015
Website