Differences between GPT-5.6 Sol, Terra, and Luna

OpenAI introduces GPT-5.6 in three main variants, namely Sol, Terra, and Luna. All three are still in the GPT-5.6 family, but are designed for different needs.

Simply put:

• GPT-5.6 Sol prioritizes capability and quality.
• GPT-5.6 Terra offers a balance between capability, speed, and cost.
• GPT-5.6 Luna prioritizes speed and lower cost.

OpenAI uses the names Sol, Terra, and Luna as tiers of model capability. Meanwhile, the number 5.6 indicates the model generation.

Summary of Differences between GPT-5.6 Sol, Terra, and Luna

Comparison	GPT-5.6 Sol	GPT-5.6 Terra	GPT-5.6 Luna
Model position	Flagship model	Balanced model	Fastest and most efficient model
Capability	Highest	High	Sufficient for simple and repetitive tasks
Speed	More focused on quality	Fast and balanced	Fastest
API Cost	Most expensive	Medium	Cheapest
Input price	$5 per 1 million tokens	$2.50 per 1 million tokens	$1 per 1 million tokens
Output price	$30 per 1 million tokens	$15 per 1 million tokens	$6 per 1 million tokens
API Model ID	gpt-5.6-sol	gpt-5.6-terra	gpt-5.6-luna
Context window	1.05 million tokens	1.05 million tokens	1.05 million tokens
Max output	128,000 tokens	128,000 tokens	128,000 tokens
Knowledge cutoff	February 16, 2026	February 16, 2026	February 16, 2026
Reasoning level	none to max	none to max	none to max
Suitable for	Complex and important tasks	Daily work	Mass and repetitive tasks
Example usage	Complex coding, research, business analysis	App development, articles, automation	Classification, summarization, data extraction
Primary priority	Quality	Balance	Efficiency

The context window, output limit, knowledge cutoff, model ID, reasoning, and price specifications above follow the official OpenAI API documentation.

What Is GPT-5.6 Sol?

GPT-5.6 Sol is the main and most powerful model in the GPT-5.6 family. This model is intended for professional work that requires deep analysis, complex reasoning, and high precision results.

Think of Sol as a senior expert. The process may be more intensive and the cost higher, but the results are usually more refined.

GPT-5.6 Sol is suitable for:

• Building complex application architectures.
• Analyzing code in large projects.
• Finding hard-to-detect bugs.
• Creating systems or features from scratch.
• Conducting deep research.
• Analyzing long data and documents.
• Assisting in business decision-making.
• Running workflows involving multiple tools.

OpenAI recommends Sol as a starting choice for work that requires complex reasoning and the best coding capabilities.

Example use of Sol

For example, you want to build a villa management system using Laravel and Next.js. The system has reservation, payment, revenue reports, Beds24 integration, pricing settings, and AI assistance modules.

Sol is better suited to help:

• Determine database structure.
• Design backend architecture.
• Create authentication and permission systems.
• Analyze inter-module relationships.
• Check application security.
• Refactor multiple files at once.

What Is GPT-5.6 Terra?

GPT-5.6 Terra is a middle option that balances capability, speed, and cost.

It is still strong for coding and professional work, but costs about half of Sol. OpenAI states that Terra's performance is competitive with GPT-5.5, but at a lower cost.

Terra is suitable for:

• Daily application development.
• Creating controllers, models, migrations, and APIs.
• Fixing Laravel or React errors.
• Writing documentation.
• Writing articles.
• Processing spreadsheets or data.
• Building internal automations.
• Running coding agents on moderately large projects.
• Conducting routine code reviews.

Think of Terra as a fast and efficient senior developer. Its capabilities may not be as high as Sol for very complex problems, but it is more than sufficient for most daily tasks.

Example use of Terra

In a Laravel project, Terra is suitable for commands like:

Create model, migration, controller, service, and API endpoint for property discount settings.

Or:

Review this controller, find possible bugs, then fix them without changing the existing business logic.

For routine use via Codex or API, Terra is likely the most sensible choice because its quality is strong while cost and speed remain manageable.

What Is GPT-5.6 Luna?

GPT-5.6 Luna is the fastest and cheapest model in the GPT-5.6 family.

This model is designed for high-volume, cost-sensitive work. In previous GPT model families, its position is roughly equivalent to the nano tier.

Luna is suitable for:

• Classifying thousands of data points.
• Extracting information from text.
• Creating short summaries.
• Converting data formats.
• Assigning tags or categories.
• Checking input formats.
• Generating large numbers of short descriptions.
• Running simple chatbots.
• Handling high-volume API requests.

Example use of Luna

For example, you have thousands of reservation records and want to group them by villa name, check-in month, booking source, or booking status.

Luna is suitable for tasks like:

Read the following reservation data and convert it to JSON with fields: property, check_in, check_out, nights, and referrer.

Luna is also suitable for generating meta descriptions for hundreds of villa pages, as long as the instructions are clear and do not require deep analysis.

Differences in API Pricing

Price is one of the most obvious differences among the three models.

Model	Input per 1 million tokens	Output per 1 million tokens
GPT-5.6 Sol	$5	$30
GPT-5.6 Terra	$2.50	$15
GPT-5.6 Luna	$1	$6

From the table:

• Terra costs about half of Sol.
• Luna's output cost is five times cheaper than Sol's.
• Sol is most suitable when quality is more important than cost.
• Luna is most suitable when the application receives a high volume of requests.

These prices apply to usage through the OpenAI API and may differ from the quota or plan system used in ChatGPT.

Are Terra and Luna Available in ChatGPT?

In standard ChatGPT conversations, Terra and Luna cannot be directly selected from the model picker. Standard conversations use GPT-5.6 Sol for reasoning options that qualify.

However, Sol, Terra, and Luna are available in several other products:

Product	Availability
Standard ChatGPT	GPT-5.6 Sol
ChatGPT Work	Sol, Terra, and Luna on qualifying plans
Codex	Terra for Free and Go; all three for certain plans
OpenAI API	Sol, Terra, and Luna

Availability depends on the plan, workspace, and the rollout process for each account.

Which One is Suitable for Coding?

For coding, the model choice should be adjusted based on the task difficulty.

Use Sol when:

• Starting a large application from scratch.
• Determining system architecture.
• Handling difficult bugs.
• Refactoring across many files.
• Working on security issues.
• Building critical features related to payments or sensitive data.
• Model failure could cause significant loss.

Use Terra when:

• Building daily features.
• Creating CRUD and APIs.
• Fixing common errors.
• Writing migrations and models.
• Writing unit tests.
• Creating documentation.
• Continuing development based on clear requirements.

Use Luna when:

• Converting simple code formats.
• Creating dummy data.
• Grouping error logs.
• Extracting information.
• Writing short comments or documentation.
• Running large numbers of repetitive processes.

Is a More Expensive Model Always Better?

Not necessarily.

Sol indeed has the highest capability, but using Sol for all tasks can be wasteful. Simple tasks like converting data to JSON do not always require the strongest model.

For example:

• For determining system architecture, use Sol.
• For developing features based on that architecture, use Terra.
• For processing thousands of data points from that system, use Luna.

This strategy keeps quality high without making AI usage costs too high.

Model Selection Recommendations

Condition	Recommended Model
Not sure where to start	Terra
Very complex and important task	Sol
Daily coding	Terra
Building an app from scratch	Sol or Terra
Fixing simple bugs	Terra
Fixing complex bugs	Sol
Processing large amounts of data	Luna
Writing high-quality articles	Terra
Deep research and analysis	Sol
High-traffic chatbot	Luna
Prioritizing lowest cost	Luna
Prioritizing best results	Sol
Want balanced quality and cost	Terra

Conclusion

The main differences between GPT-5.6 Sol, Terra, and Luna are not in their basic features, but in their usage priorities.

GPT-5.6 Sol is the best choice for complex work requiring high capability and precision.

GPT-5.6 Terra is the most balanced choice for coding, writing, application development, and daily tasks.

GPT-5.6 Luna is suitable for simple, fast, repetitive tasks with high request volume.

For most users and developers, Terra can be the primary choice. Sol is used for more difficult work, while Luna is used to reduce costs on simple and repetitive tasks.