GPT-5.6 Sol vs Terra vs Luna: Complete Comparison — Which One Should You Pick?

OpenAI launched GPT-5.6 in three variants: Sol the powerhouse, Terra the balanced workhorse, and Luna the cost champion. The difference isn't just price — it's performance, task suitability, and reasoning depth. The right question isn't "which is best?" — it's "which one fits your project?"

This comparison breaks down each model and answers the question on your mind.

The Core Difference Between the Three

GPT-5.6 follows a simple principle: match the model to the task. Stop paying flagship prices for simple jobs.

• Sol — The Flagship: Highest intelligence, complex tasks, research, advanced coding
• Terra — The Balanced: Strong performance at lower cost, great for daily work
• Luna — The Cost King: Fastest and cheapest, ideal for high volume

Pricing Comparison

• Sol: $5 input / $30 output per 1M tokens — most expensive, most capable
• Terra: $2.50 input / $15 output per 1M tokens — half the cost of Sol
• Luna: $1 input / $6 output per 1M tokens — 5x cheaper than Sol

Real example: Classifying 100,000 comments: Luna costs $110/month vs $550/month for Sol. Luna gives ~80% of the performance at 20% of the cost.

Benchmark Comparison

Coding Agent Index

• Sol: 80 — new state of the art
• Terra: ~74 — beats Fable 5
• Luna: ~65 — beats Opus 4.8

ExploitBench (Cybersecurity)

• Sol: 73.5% — leap from GPT-5.5's 47.9%
• Terra: ~55%
• Luna: ~40%

BrowseComp (Browsing & Understanding)

• Sol: 92.2% — highest recorded score
• Terra: ~83%
• Luna: ~70%

The rule of thumb: The gap between Sol and Luna is much smaller in performance than in price. Luna delivers great value for minimal cost.

When to Use Each

Use Sol when you need:

• Multi-step agentic applications
• Large coding projects (DB + API + frontend)
• Scientific research requiring deep reasoning
• Security vulnerability analysis and critical code review
• ultra mode (4 parallel agents) for massive projects

Use Terra when you need:

• Weekly reports and data analysis
• Software planning and requirements
• Long-form professional content
• Daily work assistant
• Tasks needing accuracy but not all critical

Use Luna when you need:

• High-volume text classification
• Long conversation summarization
• Data extraction from documents
• Quick first drafts
• Repetitive, well-defined tasks
• Anything you process in bulk at speed

Smart Routing Strategy (Save 50-70%)

1. Start with Luna — let the cheap model try first

2. Escalate to Terra — if Luna doesn't cut it

3. Use Sol only — for tasks that genuinely need maximum power

📊 On a $100/day project, this strategy drops costs to $30-50/day.

GPT-5.6 Sol vs Claude Fable 5

| Aspect | GPT-5.6 Sol | Claude Fable 5 |

| ------------------ | ---------------- | -------------- |

| Output price | $30/M tokens | $50/M tokens |

| Coding Agent Index | 80 | 77.2 |

| Execution speed | 2x faster | Slower |

| Multi-agent | Ultra (4 agents) | Limited |

| Browser Use | BrowseComp 92.2% | Lower |

Bottom line: Sol is cheaper and faster for coding. Fable 5 leads in visual and UI tasks.

FAQ

Is Luna faster than Sol?

Yes. Luna is optimized for speed — much lower response time than Sol. Sol takes longer because it reasons more deeply.

Terra or Sol for coding?

For simple or medium projects, Terra is enough. For complex projects (database + multi-API + UI), use Sol.

Can I use multiple models in the same project?

Absolutely. Best practice: Luna for classification and initial processing, Terra for analysis, Sol for final critical tasks.

Is GPT-5.6 Luna better than GPT-5.5?

On many tasks, yes — Luna outperforms GPT-5.5 despite being cheaper. Especially on coding and text analysis.

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📚 See the complete GPT-5.6 guide for deeper details on pricing and features.

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