OpenAI Reportedly Tests GPT-6.2 Astra as Anthropic's Mythos 5.5 Surfaces

A separate gpt-6.2-astra entry appeared in some Codex usage statistics, while the public model list still shows GPT-6 Astra; meanwhile, a Mythos 5.5 reference was noticed on Anthropic's site.
OpenAI is reportedly testing GPT-6.2 Astra in secret. Early traces of the new model were noticed in Codex usage statistics.
The public list of available models still shows GPT-6 Astra, but some users have separately seen gpt-6.2-astra in usage stats.
Anthropic seems unable to let OpenAI stay in the spotlight for even a day without trying to pull attention toward itself. As soon as the first mentions of GPT-6.2 Astra appeared, a reference to Mythos 5.5 mysteriously surfaced as well.
Anthropic page mentioning Mythos
For now, these observations are not official announcements, but they may point to early experiments with the next generation of models.
Why it matters
AnalysisIt may indicate early experiments with OpenAI's next-generation models and the competitive pace of the AI industry, where traces of testing often appear in interfaces before official releases.
Discuss in community
Share your questions and insights with developers
Related in Ecosystem
Practical guides, core terminology, and agent skills
OpenAI appears to be quietly testing GPT-6.2 Astra
Some Codex users have seen a separate gpt-6.2-astra entry in usage statistics, while the available model list still shows GPT-6 Astra.
Codex Skills for Beginners: Automating AI Agent Workflows
A comprehensive hands-on guide to building and executing Codex Skills: SKILL.md anatomy, explicit vs. auto-triggering, skills vs. scripts vs. tools, Skills API, and safety boundaries.
Claude Haiku (Fast Compact Models by Anthropic)
The most compact and fastest model in the Anthropic lineup, designed for lightning-fast responses, mass text classification, data extraction, and agent routing at minimal cost.
Claude Opus (Flagship AI Model by Anthropic)
The most powerful heavyweight model in the Anthropic family, designed for complex philosophical and scientific analysis, multi-layered text generation, and deep contextual understanding.