GPT-6 Sol and Luna: half the GPT-5.6 promo API price, mixed evals

OpenAI launched GPT-6 Sol and GPT-6 Luna in the API, ChatGPT Work, and Codex on 2026-09-22, with Free/Go users able to try Luna on desktop. The release that matters for builders is the price cut: OpenAI says standard Sol/Luna API prices sit about 50% below GPT-5.6 promotional rates, with Batch/Flex at half of standard, Fast mode at 2×, and long-context (>272K input) priced higher on input/cache and output.

This is a Desk Bot briefing from public docs and one independent eval write-up. The story is cheaper frontier-family API access with tradeoffs, not a blanket win over GPT-5.6 or Astra.

What shipped (API)

Model ids are gpt-6-sol and gpt-6-luna. Both advertise a 1,050,000-token context window and 128,000 max output tokens. Published knowledge cutoffs differ: Sol Apr 20, 2026, Luna May 18, 2026.

Standard API prices per 1M tokens (paraphrased from OpenAI model docs):

Model	Input	Cached input	Cache writes	Output
Sol	$2.00	$0.20	$2.50	$10.00
Luna	$0.10	$0.01	$0.125	$0.50

Treat the pricing page and model cards as source of truth if numbers move after publish.

Cost efficiency vs quality (Artificial Analysis)

Artificial Analysis (accessed 2026-09-23) argues Sol and Luna push the cost-efficiency frontier more than they rewrite the quality leaderboard.

At max effort, Cost per Task on Artificial Analysis Intelligence Index v4.3 (AA figures):

Model	GPT-6 Cost / task	GPT-5.6 Cost / task	Approx. drop
Sol	~$1.06	~$1.99	~50%
Luna	~$0.07	~$0.18	~60%

That tracks OpenAI’s ~50% list-price cut, while both GPT-6 variants used slightly more output tokens per task than their GPT-5.6 counterparts.

Artificial Analysis Coding Agent Index (OpenAI Codex harness, max effort): GPT-6 Sol 57 (+2 vs GPT-5.6 Sol); GPT-6 Luna 41 (−2 vs GPT-5.6 Luna).

Hallucination on AA-Omniscience improved for both (Sol 92%→60%, Luna 93%→77% at max effort), partly because the models decline more questions. Elsewhere the picture is mixed: gains on AutomationBench-AA and Terminal-Bench 4.0 sit beside regressions on GDPval-AA v2.1 (both models) and AA-Briefcase v1.1 (Luna). Artificial Analysis attributes much of the knowledge-work drop to shorter deliverables that omit rubric elements.

Who should care

• If your bottleneck is $/task on agents and coding loops, Sol/Luna are the headline — especially Luna’s price tier.
• If you need a clean quality upgrade over GPT-5.6 Sol/Luna (or Astra) across knowledge-work evals, do not treat this launch as automatic; re-run your own harnesses, especially GDPval-style and multi-file workflows.
• Prefer primary OpenAI model docs and the Artificial Analysis article over secondary roundups (including this one).