OpenAI releases GPT-5.6 family in three sizes: Luna at $1/$6, Terra at $2.50/$15, Sol at $5/$30 per 1M tokens
OpenAI released its GPT-5.6 flagship model family in three sizes: Luna ($1/$6 per 1M tokens), Terra ($2.50/$15), and Sol ($5/$30). The company claims GPT-5.6 Sol scores 53.6 on the Agents' Last Exam benchmark, outperforming Claude Fable 5's score by 13.1 points.
GPT-5.6 Sol — Quick Specs
OpenAI released its GPT-5.6 flagship model family with three models sized from smallest to largest: Luna, Terra, and Sol. All three models are now generally available.
Pricing Structure
Input and output pricing per 1M tokens:
- GPT-5.6 Luna: $1 input / $6 output
- GPT-5.6 Terra: $2.50 input / $15 output
- GPT-5.6 Sol: $5 input / $30 output
For comparison, Claude Opus costs $5/$25 per 1M tokens and Claude Fable 5 costs $10/$50. However, direct price comparisons are complicated by varying reasoning token usage across models for identical tasks.
Benchmark Performance
OpenAI claims GPT-5.6 Sol achieves 53.6 on the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields. According to OpenAI, this beats Claude Fable 5's adaptive reasoning mode by 13.1 points. At medium reasoning, Sol reportedly outperforms Fable 5 by 11.4 points at roughly one-quarter the estimated cost.
OpenAI states that GPT-5.6 Terra and Luna outperform Fable 5 at approximately one-sixteenth the cost.
On SWE-Bench Pro, GPT-5.6 Sol scored 64.6% compared to Claude Fable 5's reported 80%. One day before the GPT-5.6 release, OpenAI published an analysis questioning SWE-Bench Pro's validity, estimating that approximately 30% of tasks are broken and advising developers to "carefully examine results."
New API Features
GPT-5.6 introduces several API capabilities:
Programmatic Tool Calling: Models can compose and run JavaScript to orchestrate tool calls, similar to Anthropic's dynamic filtering mechanism for web search.
Multi-agent: Native support for spinning up subagents for parallel, focused work.
Prompt cache breakpoints: Explicit control over cache breakpoints, following Claude's model. Automatic detection remains supported.
Image detail control: Setting detail: original prevents image resizing before processing.
What This Means
The three-tier release strategy positions OpenAI to compete across different cost-performance requirements. Luna and Terra target cost-sensitive applications while Sol competes directly with Claude Opus and Fable 5 at the high end. The timing of OpenAI's SWE-Bench Pro critique—published one day before a release where their model underperforms on that specific benchmark—raises questions about benchmark selection and methodology. Early user reports suggest GPT-5.6 Sol performs comparably to, but not necessarily better than, Claude Fable 5 on complex coding tasks.
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