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Article · 2026-07-09 · 6 moments

The new GPT-5.6 family: Luna, Terra, Sol

OpenAI's latest flagship model hit general availability this morning, and comes in three sizes: Luna, Terra, and Sol (from smallest to largest). The new models are priced per 1M input/output tokens as Luna $1/$6, Terra $2.50/$15, Sol $5/$30. For comparison, the Claude Opus series are $5/$25 and the Claude Fable 5 is $10/$50, but price-per-million tokens doesn't tell us much now that the number of reasoning tokens can differ so much between models for the same task. OpenAI's biggest benchmark c ✦ AI generated

01
Data

A pelican-riding-a-bicycle benchmark page of 18 images across six reasoning efforts and three GPT-5.6 models shows costs ranging from 0.71 cents (Luna, no reasoning) to 48.55 cents (Sol, max reasoning).

Simon Willison's pelican benchmark page tracks token costs across GPT-5.6 model sizes and reasoning efforts, ranging nearly 70x from cheapest to most expensive.

transcript

Simon Willison: Here's a full page with 18 different pelicans - for reasoning efforts none, low, medium, high, xhigh, and max across the three different models. It also lists their token and calculated costs - the least expensive was gpt-5.6-luna at effort none for 0.71 cents, the most expensive was gpt-5.6-sol at max reasoning level for 48.55 cents.

provides context · 1

02
Claim

Claude Fable 5 beat GPT-5.6 Sol badly on SWE-Bench Pro (80% vs 64.6%), a result OpenAI downplays by claiming roughly 30% of SWE-bench Pro tasks are broken and urging developers to scrutinize results carefully.

Fable 5 crushed the GPT-5.6 family on SWE-Bench Pro, and OpenAI published a separate audit the day before claiming ~30% of that benchmark's tasks are broken, casting doubt on the result.

transcript

OpenAI: In light of these results, we estimate that ~30% of SWE-bench Pro tasks are broken, and advise that model developers carefully examine results

03
Fact

GPT-5.6 launched today in three sizes—Luna, Terra, and Sol—priced at $1/$6, $2.50/$15, and $5/$30 per million input/output tokens respectively, though such pricing comparisons are of limited value given differing reasoning-token usage across models.

GPT-5.6 ships in three tiers (Luna, Terra, Sol) with escalating prices, but the author notes raw per-token pricing is misleading since reasoning-token usage varies by model.

transcript

Simon Willison: The new models are priced per 1M input/output tokens as Luna $1/$6, Terra $2.50/$15, Sol $5/$30. For comparison, the Claude Opus series are $5/$25 and the Claude Fable 5 is $10/$50, but price-per-million tokens doesn't tell us much now that the number of reasoning tokens can differ so much between models for the same task.

provides context · 1

05
Data

GPT-5.6 Sol sets a new high score of 53.6 on the Agents' Last Exam benchmark, beating Claude Fable 5 by 13.1 points, and even at medium reasoning it beats Fable 5 by 11.4 points at roughly a quarter of the cost.

OpenAI touts GPT-5.6 Sol's performance on Agents' Last Exam, a 55-field long-running professional workflow benchmark, as decisively beating Claude Fable 5, with smaller GPT-5.6 models also beating Fable 5 at much lower cost.

transcript

OpenAI: On Agents' Last Exam, an evaluation of long-running professional workflows across 55 fields, GPT-5.6 Sol sets a new high of 53.6, eclipsing Claude Fable 5 (adaptive reasoning) by 13.1 points. Even at medium reasoning, it beats Fable 5 by 11.4 points at roughly one-quarter the estimated cost.

rebuts · 1

06
Mechanism

OpenAI's new Programmatic Tool Calling feature lets GPT-5.6 models compose and run JavaScript that orchestrates tool calls, which could help bridge the gap between MCP-style tool use and full terminal sessions composing CLI utilities.

GPT-5.6 adds Programmatic Tool Calling, letting the model generate and execute JavaScript to orchestrate tool calls, a mechanism the author compares to Anthropic's code-execution-enabled web search tool.

transcript

Simon Willison: Programmatic Tool Calling allows the models to "compose and run JavaScript that orchestrates tool calls" - which sounds to me like it could help bridge the gap between MCPs and full terminal sessions that can compose CLI utilities in useful ways. Also reminiscent of the dynamic filtering mechanism Anthropic added to their web search tool, which allows code execution against web results as part of a single model turn.

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