GPT-6 Sol and Luna landed on September 22, 2026, and the interesting number is not on any benchmark chart. It is on the pricing page. GPT-6 Sol costs $2.00 per million input tokens and $10.00 output. The model it replaces, GPT-5.6 Sol, is $4.00 and $20.00. That is half, on both sides of the meter. The capability story is thinner. The only independent measurement published on launch day puts GPT-6 Sol one point above its predecessor, and GPT-6 Luna two points below its own.

On September 3, 2026, ARC Prize published two scores for the same model on the same benchmark on the same day. GPT-6 Astra scored 62.7% on arc-agi-3 under the standard, provider-neutral harness, and 99.9% under a harness supplied by OpenAI. Both numbers are real. Both were produced by the organization that runs the benchmark. ARC Prize says it will report both, labeled.

MiniMax M3 is an open-weight large language model from the Chinese AI lab MiniMax, released at the end of May 2026 with a context window of roughly one million tokens. It is built for agentic coding and long-document work, it ships under a permissive but not fully open-source license, and it undercuts most Western frontier models on price by a wide margin.

GPT-6 Astra landed on September 3, 2026, and the announcement page is doing several jobs at once. Some of what it describes is generally available in the API today. Some is capability-complete but gated behind a limited rollout. Some is behind an opt-in flag in a config file. And some is a name attached to a plan with no date, no criteria, and no definition.

The OpenAI training pause reported on August 18, 2026 is the first time a major lab has publicly stopped a flagship training run because a model's offensive security capability crossed a line the lab had drawn for itself. Two weeks of reinforcement learning training on deployment-bound models were halted, and the largest planned frontier run remains on hold. The reporting has focused on how alarming that is.