Muse Wonder
Meta's first frontier-class model — an agentic flagship built around persistent memory and long tasks.
About
Muse Wonder (released Oct 12, 2026) is the first frontier-class model from Meta's Superintelligence Labs, succeeding the lightweight Muse Spark line (Spark 1.3 scored 48 on the AA Intelligence Index six weeks earlier). It ships as two variants: Muse Wonder (model id muse-wonder-1.0, available via the Meta Model API and Muse Code) and Muse Wonder Full (stronger; Muse Code subscribers only — no API access or public price). The pitch is agentic work: "Active Memory" carries facts across conversations, and "Active Focus" keeps the model working through blockers and checking in before consequential actions. It accepts text, images, video, and audio. Unlike the Llama era, Wonder is closed — no weights release announced. It is positioned as the model that will power Meta's Muse personal agent (rolling out to subscribers first).
Specs
Context window
Pricing
Free quota
API access
Weights
Released
Benchmarks
Provider-reported (Meta, model card): Meta's charts put Wonder Full ahead on several agent/coding benchmarks, e.g. 57.5% on Meta's SWE-Marathon (long-running software benchmark) vs 46.3% for Claude Opus 5.5; Meta also claims a lead on MemoryBench (continual-learning/recall) over Fable, Opus, and Astra.
Independent: Artificial Analysis Intelligence Index v4.3 scores Muse Wonder Full at 56 (second on the index, behind Claude Opus 5.5 at 58, ahead of GPT-6 Astra and Gemini 4 Argon at 53) and the standard Muse Wonder at 52; Full finished top-three on six of the ten index evaluations. AA pegs cost at $4.52 per benchmark task (vs $1.60 for Muse Spark 1.3). Independent hands-on coverage is still thin — the model is one day old — and Meta's safety report is promised but not yet published (vandatateam).
Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.
Use cases
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: provider-tier estimate — thinner evidence (no public adoption metric); just launched; no public adoption metric; released 1 days ago. Manual review: one day old; ~1M context from third parties; safety report unpublished; Wonder Full has no API. License: closed weights.
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 8.0/10
- Maintenance · recency, releases, issue load
- 9.0/10
- Openness · license + docs
- 5.1/10
- Manual review · sanity read + red-flag check
- 8.0/10
- · provider-tier estimate — thinner evidence (no public adoption metric)
- · just launched; no public adoption metric
- · released 1 days ago
- · manual review: one day old; ~1M context from third parties; safety report unpublished; Wonder Full has no API