GPT-5.6 - OpenAI's latest-generation large language model series

What is GPT-5.6

GPT-5.6 is the latest-generation large language model released by OpenAI. For the first time, the model adopts an astronomical naming system, offering three tiers: the flagship version Sol(Sun) is aimed at highly difficult and complex tasks and is currently the most powerful version; the balanced version Terra(Earth) matches GPT-5.5 in performance but costs only half as much, making it suitable for everyday workflows; the lightweight version Luna(Moon) focuses on speed and low cost. Its core capabilities focus on three major directions: programming, bioinformatics, and cybersecurity. It supports a super-long context of 1.5 million tokens and leads across the board in benchmarks such as Terminal-Bench and GeneBench. The newly added Ultra mode handles complex tasks through collaboration among multiple sub-agents.

Main features of GPT-5.6

• Flexible choice of three tiers: Provides three versions, Sol (flagship), Terra (balanced), and Luna (lightweight), corresponding respectively to highly difficult tasks, everyday work, and low-cost high-concurrency scenarios.
• Super-long context processing: Supports a 1.5 million token context window and can handle extremely long documents, codebases, and complex multi-turn conversations.
• Advanced programming and terminal operations: Executes complex development tasks in command-line environments, supporting project structure understanding, file reading, code modification, command execution, and error analysis.
• Ultra mode multi-agent collaboration: Splits complex tasks for processing by scheduling multiple sub-agents and aggregates the results uniformly, improving efficiency for long-cycle coding.
• Bioinformatics and genomic analysis: Supports long-cycle genomics and quantitative biological analysis tasks, achieving stronger results with fewer output tokens.
• Cybersecurity and vulnerability research: Advances long-cycle security tasks, including vulnerability research and exploitation-related tasks, with significantly improved efficiency.
• Layered security protection system: Strengthens protection against high-risk activities, sensitive network requests, and repeated abusive behavior, defending against real-world attacks.
• Prompt caching and cost optimization: Optimizes the mechanism for repeated prompt calls and reduces API usage costs in high-frequency scenarios.

How to use GPT-5.6

• ChatGPT: Plus/Pro/Business/Enterprise users can access Sol (medium effort and above), and Pro and Enterprise can choose Sol Pro.
• ChatGPT Work/Codex: Free and Go users use Terra; Plus and above can choose Sol/Terra/Luna and can set the effort level; max mode can be enabled by all users who have access; ultra is available to Pro/Enterprise in ChatGPT Work and to Plus and above in Codex.
• API: Access the three model tiers through the OpenAI API. The Responses API supports Programmatic Tool Calling (ZDR-compatible) and Multi-agent beta.

GPT-5.6 official website address

• Official website address：https://openai.com/index/gpt-5-6/

Core advantages of GPT-5.6

• Flexible matching through three tiers: Sol (flagship), Terra (balanced), and Luna (lightweight) cover highly difficult tasks, everyday work, and low-cost high-concurrency scenarios, allowing on-demand selection without wasting compute.
• Industry-leading programming capability: On Terminal-Bench 2.1, Sol scores 88.8% and Sol Ultra 91.9%, surpassing competitors such as Claude Mythos 5 (88.0%).
• Super-long context window: Supports 1.5 million tokens, an increase of about 50% over GPT-5.5, and can handle complete codebases, long documents, and complex multi-turn conversations.
• Ultra Mode Multi-Agent Collaboration: Automatically orchestrates multiple sub-agents to split and process complex tasks in parallel, then unifies and summarizes the results, greatly improving long-cycle coding efficiency.
• Dual Excellence in Research Cost and Efficiency: On GeneBench v1, Sol scores higher than GPT-5.5 but outputs fewer tokens, making bioinformatics analysis more cost-effective.
• Efficient and Precise Cybersecurity: On ExploitBench, it approaches the level of Mythos Preview but uses only about 1/3 of the output tokens, significantly improving vulnerability research efficiency.
• Layered Security Protection System: The strongest security stack to date, capable of defending against high-risk activities, sensitive network requests, and real-world attacks.
• Reasonable Price Tiers: Terra's performance is comparable to GPT-5.5 but at only half the price; Luna has the lowest cost; the prompt caching mechanism further reduces the overhead of repeated calls.

Comparison of Similar Competitors to GPT-5.6

Application Scenarios for GPT-5.6

• Complex Software Development and Terminal Operations: Executes complex coding tasks deep within command-line environments, including project structure understanding, file reading, code modification, running commands, error analysis, and iterative fixes, suitable for large codebase refactoring and full-stack development.
• Bioinformatics and Genomic Research: Handles long-cycle genomics analysis and quantitative biological analysis tasks, maintaining context consistency across multiple rounds of data interpretation, method selection, and hypothesis comparison, suitable for laboratories and biomedical R&D teams.
• Cybersecurity and Vulnerability Research: Executes long-cycle security tasks, including vulnerability discovery, exploitation research, and penetration testing, achieving efficient analysis with lower token consumption.
• Enterprise Daily Office Automation: Handles high-frequency daily workflows such as document analysis, report writing, and data organization through the Terra version, with performance comparable to GPT-5.5 but at half the cost.
• High-Concurrency, Low-Cost Inference Services: Carries large-scale, high-volume call scenarios such as customer service chatbots, content summarization, and simple Q&A through the Luna version, providing strong foundational capabilities at the lowest price.
• Ultra-Long Document Deep Analysis: Process full technical manuals, legal contracts, academic papers, or large codebases with a 1.5 million token context window for full-text understanding and cross-chapter correlation analysis.