The confusion is real. People search for "GPT 2.5 pricing" and "GPT 2.5 pro" every day. OpenAI doesn't have a GPT 2.5. Instead, the current lineup is a maze: GPT-5.4, GPT-5.5, GPT-5.6 in three tiers (Sol, Terra, Luna), plus GPT-6 Astra launched last week.
The naming makes sense only if you've been following OpenAI's releases monthly since January. For everyone else, it's chaos. Here's what you actually need to know.
The Current Lineup (September 2026)
GPT-6 Astra (Latest, just launched) - Cutting-edge reasoning and coding - Flagship model, highest cost - Use only if cost doesn't matter and you need maximum capability GPT-5.6 Sol (Current flagship budget option) - $5.00 / $30.00 per million tokens - Best all-arounder for most workloads - The model to pick if you're unsure GPT-5.6 Terra (Mid-tier value) - $2.00 / $12.00 per million tokens - 40% cheaper than Sol, barely noticeable performance difference - Good choice for cost-conscious production GPT-5.6 Luna (Budget option) - $1.00 / $6.00 per million tokens - 80% cheaper than Sol at launch - Fast enough for most tasks, capable enough for production GPT-5.5 (Previous flagship) - $5.00 / $30.00 (same price as Sol now) - Slightly less capable than GPT-6 Astra - No reason to use this anymore — Sol costs the same GPT-5.4 (Two generations back) - $2.50 / $15.00 per million tokens - Still solid for production, noticeably slower than 5.6 - Use only if you're already on it and migrating costs more than saving
The Decision Framework
If you're building something new: Start with GPT-5.6 Luna ($1/$6). It's cheap, fast, and capable. Only upgrade to Terra or Sol if Luna's speed becomes a bottleneck.
If you need maximum capability: Use GPT-6 Astra if cost is irrelevant. Otherwise, Sol is the practical flagship.
If you're cost-optimizing existing code: Terra gives you 40% savings for imperceptible quality loss. Luna gives you 80% savings for noticeable but acceptable loss. Pick the tradeoff that matches your margins.
If you have old models running in production: Leaving GPT-5.4 in place costs you nothing to migrate, but migrating to Luna saves you 50% per token. The math often favors switching.
Why OpenAI's Naming Is Confusing
OpenAI released GPT-5.6 in July with three tiers (Sol, Terra, Luna), then cut Luna's price 80% in late July. That's why people search for "GPT 2.5" — they remember an older version number and don't realize the lineup has moved to 5.6. GPT version numbers don't tell you when a model was released; the date does. Sol, Terra, and Luna are released on the same day but perform differently.
There is no roadmap that says "here's when to upgrade." You upgrade when the savings or capability bump justify migrating your code. For many teams, that's every 3-4 months. For others, it's "when someone notices performance issues."
Practical Pricing Comparison
For a typical 100M token/month workload (100K input + output split):
| Model | Monthly Cost |
|---|---|
| Luna | $300 |
| Terra | $600 |
| Sol | $1,000 |
| Astra | $3,000+ |
Luna costs $700 less than Sol per month. If you have 10 services, that's $7,000/month in savings by switching. For most startups, that's real money.
The Bottom Line
There's no "best" model. There's the right tradeoff of cost, speed, and capability for your workload. Most founders should pick Luna (cheap, good enough), upgrade to Terra if they see speed issues, and only use Sol for workloads that genuinely need the extra power.
GPT-6 Astra is the cutting edge. It's also 3x the price of Sol. Save it for problems you can't solve with 5.6.