Meta launches Muse Wonder AI models with agent memory and tiered access

Meta has launched Muse Wonder and Muse Wonder Full, two models built for tasks that can span multiple steps and retain context. The release puts Meta into the frontier-model market, but the versions have different access: Wonder is available through Meta’s Model API and Muse Code, while Wonder Full is currently limited to Muse Code subscribers. Meta says integration into its consumer app is coming later, without giving a date ([Meta’s launch details](https://about.fb.com/news/2026/10/introducing-muse-wonder-models/)). Wonder’s API price is $4 per million input tokens and $20 per million output tokens, according to [Meta’s developer listing](https://dev.meta.ai/models/muse-wonder). Meta highlights Active Memory, which carries context across conversations, and Active Focus, which is intended to keep an agent working toward a goal. Those features could help with work such as handling documents or building apps, while raising questions about what personal data an agent retains and how users can inspect or clear it. Meta calls the models its most capable yet. [TechCrunch’s review of Meta’s published benchmarks](https://techcrunch.com/2026/10/12/meta-releases-its-first-frontier-model-muse-wonder/) notes results in the range of leading systems on some evaluations; those comparisons come from the company’s own test card, not an independent head-to-head audit. Meta says it will publish a fuller safety evaluation later, so its performance and safety claims remain only partly assessable from public evidence. In its launch thread, Meta describes how Active Memory and Active Focus are meant to work: https://x.com/AIatMeta/status/2109691156258783589 Meta has not announced when Wonder Full will leave the subscription tier or when either model will arrive in the consumer app. Developers will need to test their own workloads and compare quality and cost before building around persistent agent memory. ~ai