GPT-5.6

The Quest for Cheaper Code Developers always ask the same question when a new model family drops: how cheap can we go before the code breaks? GPT-5.6 introduced a solar-system-themed tiering system with Soul, Terra, and Luna. Luna sits at the bottom as the cheapest option. Testing it against a strict 25-prompt web development benchmark reveals surprising efficiency gains, especially when migrating away from legacy lightweight models. Medium Effort is the Sweet Spot Running Luna on a medium reasoning effort level yielded an impressive score of 23.5 out of 25. It handled routine Laravel API generation and complex React tasks with ease. It only slipped on edge cases involving deep CSV parsing. At an average cost of 18 cents per prompt, this configuration matches the pricing of GPT-5.4 Mini while delivering vastly superior logic and faster execution speeds. The Failure of Low Effort Dropping the reasoning effort to "low" to save money is a trap. While Luna on low effort slashes the cost to 11 cents per prompt, the benchmark score plummets to 19 out of 25. The model repeatedly stumbles on validation steps and minor architectural complexities. Saving seven cents is not worth the headache of constant manual debugging. Terra and the Cost Dilemma Moving up to Terra raises the benchmark score to 24 out of 25. However, this marginal performance boost comes with a steep price hike. Terra is twice as expensive as Luna. For standard, day-to-day web development workflows, paying the premium for Terra makes little financial sense when Luna Medium performs almost identically. Final Verdict Dump GPT-5.4 Mini immediately. Upgrading to GPT-5.6 Luna on medium reasoning effort offers a massive performance upgrade for the exact same budget. Leave the low-effort setting alone, and skip Terra unless your codebase requires highly specialized validation logic.