Advancing the price-performance frontier with GPT‑5.6

Simon Willison · Simon Willison · 30 July 2026, 23:58 ● Covered by 10 sources

OpenAI cut prices for GPT-5.6 models, with Luna dropping 80% and Terra dropping 20%, using GPT-5.6 Sol to optimize inference and kernel performance. GPT-5.6 Luna now costs $0.20 per million input tokens and $1.20 per million output tokens, undercutting competitors like Google's Gemini 3.1 Flash-Lite and Anthropic's Claude Haiku 4.5. The pricing changes make Luna competitive for cost-sensitive applications, prompting developers to migrate from other models.

Why it matters

Advancing the price-performance frontier with GPT‑5.6 Huge price drop from OpenAI today: GPT-5.6 Terra got a 20% reduction, and GPT-5.6 Luna got a massive 80% drop. OpenAI credit 5.6 Sol with enabling this: in How GPT‑5.6 fuses frontier intelligence with frontier efficiency they describe using 5.6 Sol to optimize load balancing, and more impressively to optimize inference itself: We also used GPT‑5.6 Sol to optimize the model’s forward pass: the computation that transforms inputs into next-token predictions. Even when individual operations are fast, excess memory movement, synchronization, and inefficient data layouts can leave GPUs idle. To avoid this, GPT‑5.6 Sol found work that could be precomputed, avoided, or parallelized. With Codex, GPT‑5.6 Sol autonomously rewrote and optimized our production kernels, the core code that executes the mathematical operations that make up the model. This worked in part because we’ve trained GPT‑5.6 to be effective at writing and improving kernels