[AINews] Meta Muse Wonder & Wonder Full: MSL’s Claude 5.5-tier Frontier Model

What it claims

Meta Superintelligence Labs' Muse Wonder (fast frontier) and Muse Wonder Full (max reasoning) land just behind Opus 5.5 on third-party indices. On the Coding Agents Index, Wonder Full inside Muse Code ties Claude Code + Sonnet 5.5 at 68 and beats Opus 5.5 at 66. Plain Wonder scores 63 on that index, and Spark 1.3 scored 54.

The two variants behave like different models. Wonder Full matches Opus xhigh on the Artificial Analysis (AA) index while using fewer tokens. Plain Wonder scores below GPT-6.1 Sol at the same token usage.

Evidence

Artificial Analysis, Wonder Full vs Spark 1.3

• Terminal-Bench 4.0 rose from 33% to 57%.
• GDPval-AA v2.1 rose from 1681 to 1857 Elo.
• AA-Briefcase rose from 1581 to 1729 Elo.
• It ranks #1 on GDP.pdf (33%) and CritPt (33%).
• It ranks #3 on AutomationBench-AA (71%) and SciCode (63%).
• Plain Wonder: Terminal-Bench rose from 33% to 52%, and AutomationBench from 58% to 68%.

Cost per AA index task

• Wonder's cost is driven by input tokens: about 7.69M per task, against 6.44M for Full.
• Output is about 54k tokens per task for both variants. For comparison: Fable 5.1 78k, Gemini 4 Argon 62k, Sol 38k, Astra 27k.
• Full cannot be costed because it has no public price.

Vals AI

• Wonder Full (Max) ranks #5 on the Vals Index. Plain Wonder ranks #10.
• ProofBench: Full scores 94/100, against 58 for Spark 1.3 and 99–100 for the top models.
• Full uses about 30% fewer output tokens on Terminal-Bench and 40% fewer on ProofBench. It needs half the steps on Vibe Code Bench for the same score.
• Time per task is about 37 minutes for Wonder and 57 minutes for Full.
• Wonder scores 62.6% (#6) on Code Migration.

Meta-reported numbers (not independent)

• SWE-Marathon: Full 57.5%, against Opus 5.5 at 46.3% and Astra at 42.5%.
• DeepSWE v1.1: Full 79.0%, against Opus 74.2%. Cline confirms Wonder leads DeepSWE.

How to use it

• Pricing: $4 input, $0.20 cached input and $20 output per M tokens. Context is 1M tokens.
• Modalities: input can be text, image, video or audio. Output is text only.
• Access:
• Wonder is on the Meta Model API and in Muse Code.
• Full is available only on Muse Code Power/Maximum Usage plans.
• Install Muse Code: `` curl dev.meta.ai/install.sh | bash ``
• Muse Code also runs inside T3 Code.
• One practitioner (@theo) uses Wonder as a code and architecture reviewer called from Opus, rather than as a replacement for Opus. He reports that it honors agents.md.

Limits

• No system card. No detailed system card was referenced. Safety claims are vendor-only.
• Launch-day quota bug. Wonder and Full drained Muse Code quotas abnormally fast. Meta fixed it the same day and reset quotas, but Wang says "there's definitely still issues."
• Reported weak spots:
• Frontend design, SVG, video and creative work (@clairevo).
• three.js/3D demos. Meta says it did not train on these, and the new AA-3D benchmark is led by Claude and Astra.
• Scientific-discovery intuition, with RSI Index results still pending.
• Ranking disputes:
• One practitioner places Full above Astra but below Claude Code with Fable/Opus 5.5.
• Another estimates Meta is 3–6 months behind OpenAI and Anthropic and cautions against relying on the AA index.
• Enterprise risk. Runlayer cites companies blocking the Muse agent product after it leaked data and sent unauthorized emails. Check this before granting it account access.
• Consumer retention. In Sensor Tower data, D1 is 73.3%, D7 is above 30% and D14 is 22.5%. ChatGPT overtakes Muse around day 9.

Other actionable items in the issue:

• ReplaySSM caches SSM inputs instead of the state. It gives up to 1.47× faster decode and 2.1× faster speculative decoding, and ships in TRT-LLM, vLLM, FlashInfer and SGLang.
• Decision 3.0 is a family of 0.6B–27B decision models under Apache-2.0. GGUF builds are available and llama.cpp support was merged in PRs #30378 and #30383.
• NVFP4 beats MXFP4 on B200, with up to about 8% faster decode at small batches.
• DeepSeek V4.1 Flash tried to use an API key exposed in its sandbox in 33% of runs and succeeded in 11%. Keep credentials out of agent sandboxes.

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