GPT-5.6 Sol vs GPT-5.6 Terra: The 2x Price Fight
My verdict: GPT-5.6 Terra is the cleaner default for production teams watching spend, while GPT-5.6 Sol only makes sense if your own evals show a quality jump. The tape is brutal on cost: Sol charges exactly double Terra on both input and output, with no supplied benchmark win to soften the blow.
Price: Terra lands the first hard shot
Here’s the cleanest punch of the matchup: GPT-5.6 Sol is priced at $5.00/1M input tokens and $30.00/1M output tokens. GPT-5.6 Terra comes in at $2.50/1M input and $15.00/1M output.
That’s not a small premium. It’s a straight 2x bill on both sides of the meter. If you’re running summarization, extraction, routing, customer support drafts, or internal copilots at volume, Terra starts every round with a huge advantage.
Benchmarks: Sol needs proof, not aura
The current benchmark chatter is crowded: GPT-5.5, Gemini 3, Grok 4, and Claude Opus are all showing up across FrontierMath, GPQA, SWE-Bench, AIME, and Humanity’s Last Exam discussions. Claude Opus is cited at 94.6% on GPQA Diamond and 93.9% on SWE-Bench.
But for this specific fight, the supplied material gives no exact benchmark score for GPT-5.6 Sol or GPT-5.6 Terra. That matters. At double the price, Sol needs hard evidence: better pass rates, fewer retries, stronger agent behavior, or lower human review time. Without that, the premium is taking punches.
Production fit: Terra is the safer rollout model
The broader industry angle today is production, not flashy demos. That lines up with Terra’s case. Cheaper tokens mean more room for retries, eval runs, logging, and guardrail passes before the invoice starts biting.
Sol may still be the right pick for narrow high-value workflows: complex coding agents, long reasoning chains, or tasks where one better answer beats five cheaper attempts. But you should make Sol win that spot in your own test set.