GPT 5.5
OpenAI's natively omnimodal, agentic model processing text, image, audio, and video end-to-end, with a 1M-token context window and native computer use, leading coding and knowledge-work benchmarks for autonomous agents and research.
- Modalities
- Chat
- Starting price
- From $22.5 / 1M out
- Context
- 1.1M context
OpenAI
README
Supported Functionality
| Item | Specification |
|---|---|
| Input | Text, Image |
| Output | Text |
| Context | 1,050,000 tokens |
| Max Output | 128,000 tokens |
| Vision | ✓ Supported |
| Function Calling | ✓ Supported |
Description
GPT-5.5 is OpenAI's professional reasoning and coding model, released on April 24, 2026. At launch, it was positioned as a frontier model for the most complex professional work, with a focus on coding, tool-heavy agents, grounded assistants, and long-context workflows.
Compared with prior models, it can reach strong results with fewer reasoning tokens and improves outcome-oriented execution, constraint preservation, tool selection, and argument accuracy. It also enhances default image detail, long-running state compaction, and output-style control, while the Responses API provides prompt caching, tool search, computer use, Hosted Shell, Apply Patch, Skills, MCP, and other capabilities.
Key Capabilities
- Complex Reasoning: Five reasoning-effort levels—
none,low,medium,high, andxhigh—let developers balance quality, latency, and cost by task difficulty. - Software Engineering and Coding: Strong planning, repository navigation, tool use, modification, and verification support multi-step, testable engineering tasks.
- Long-Running Agents: More precise tool selection and arguments on large tool surfaces, combined with compaction and state management, support sustained execution.
- Long-Context Retrieval: A 1,050,000-token context can hold large codebases, document collections, and multi-turn state, with up to 128,000 output tokens.
- Vision and Computer Interaction: Image input preserves more visual detail by default under
autoand can pair with Computer Use for interface understanding and operation. - Instruction Following and Execution: The model can work from goals, success criteria, and constraints to choose an execution path and turn product intent into concrete plans and results.
- Structured Professional Output: Structured Outputs and configurable
text.verbositysupport clear, direct, JSON Schema-compliant responses.
Technical Strengths
| Feature | Benefit |
|---|---|
| Efficient Reasoning | Achieves strong results with fewer reasoning tokens at the same effort level, reducing cumulative consumption in complex multi-step workflows. |
| Precise Tool Use | More accurate tool selection and arguments on large tool surfaces help reduce incorrect calls and agent workflow failures. |
| 1.05M-Token Context | Handles large repositories and long source collections in one request, reducing information loss from chunking. |
| Original Image Detail by Default | Under auto, images can remain unscaled within documented limits, preserving visual information needed for interface understanding and computer use. |
| Compaction and State Management | Compresses long conversations while preserving important task state, helping long-running agents continue effectively. |
| Broad Hosted Tool Ecosystem | Web Search, File Search, Code Interpreter, Hosted Shell, Computer Use, MCP, and Skills support a retrieval-to-action workflow. |
Pricing
Token-based pricing
Tiered by input prompt tokens (incl. cache): once over the threshold, the whole request is billed at the higher tier.
| Token Type | Short context ≤272K | Long context >272K |
|---|---|---|
| Input | $3.75$5-25% | $7.5$10-25% |
| Output | $22.5$30-25% | $33.75$45-25% |
| Cached input | $0.375$0.5-25% | $0.75$1-25% |