GPT 5.6 Terra
OpenAI's next-generation general-purpose model balancing intelligence and cost, featuring long-context reasoning, multimodal understanding, and full agent tooling for enterprise AI, coding, automation, and professional knowledge work.
- Modalities
- Chat
- Starting price
- From $0.15 / call
- 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-5.6 Terra is the balanced model in OpenAI's GPT-5.6 family, released on July 9, 2026 for production workloads that value both intelligence and cost. It roughly corresponds to the mini tier in earlier GPT-5 families.
At a lower price than the flagship tier, the model retains a 1,050,000-token context window, a 128,000-token maximum output, six reasoning-effort levels, image understanding, function calling, and Structured Outputs. As part of the GPT-5.6 family, it also supports persisted reasoning, Programmatic Tool Calling, explicit prompt caching, multi-agent orchestration in beta, and Responses API tools for retrieval, code execution, computer interaction, MCP, and Skills.
Key Capabilities
- Balanced Deep Reasoning: Delivers strong reasoning below flagship pricing for production tasks that require consistent quality at scale.
- Configurable Reasoning Effort: Supports
none,low,medium,high,xhigh, andmaxto control quality, latency, and consumption by task difficulty. - Software Engineering and Coding: Code Interpreter, Hosted Shell, Apply Patch, and Skills support code understanding, modification, execution, and verification.
- Long-Context Processing: A 1,050,000-token context can hold large codebases, document collections, and persistent task state, with up to 128,000 output tokens.
- Agent and Tool Orchestration: Function calling, Programmatic Tool Calling, MCP, tool search, and multi-agent orchestration support complex automated workflows.
- Vision Understanding: Image input and
originalimage detail support interface screenshots, charts, scanned documents, and high-resolution material. - Structured and Retrieval-Augmented Work: Structured Outputs, Web Search, and File Search can transform external information into reliable JSON Schema-compliant results.
Technical Strengths
| Feature | Benefit |
|---|---|
| Intelligence-Cost Balance | Current rates of $2 per million input tokens and $12 per million output tokens provide strong capability for production deployments with quality and budget requirements. |
| Six Reasoning Levels | Simple tasks can use less reasoning for speed, while difficult tasks can receive more reasoning effort for higher quality. |
| 1.05M-Token Context | Processes large codebases and long source collections in one request, reducing information loss and engineering overhead from chunking. |
| Persisted Reasoning | Reuses reasoning state across turns and consecutive tool calls, reducing repeated computation and improving workflow continuity. |
| Programmatic Tool Calling | Allows tools to be invoked during code execution, shortening round trips in complex agent tasks. |
| Broad Hosted Tool Ecosystem | Web Search, File Search, Hosted Shell, Computer Use, MCP, and Skills cover a complete retrieval-to-action workflow. |
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 | $1.5$2-25% | $3$4-25% |
| output | $9$12-25% | $13.5$18-25% |
| cache_read | $0.15$0.2-25% | $0.3$0.4-25% |
| cache_write | $1.875$2.5-25% | $3.75$5-25% |