Meta’s Muse Wonder IS OPUS 5.5 LEVEL?! I Don’t Think So... (Fully Tested)

Summary
The presenter from the YouTube channel World of AI provides an independent benchmark evaluation and critical review of Meta’s newly launched frontier AI models, Muse Wonder and Muse Wonder Full. He compares their real-world coding, 3D graphics, and frontend generation performance against Meta’s claims and rival models such as Claude Opus 5.5, Claude Fable 5.1, and SWE 2. While acknowledging strengths in token efficiency and agentic planning, he argues that Muse Wonder falls significantly short of Meta’s hype in complex programming and interactive rendering.

What is shown

• [00:33] The World of AI leaderboard displaying Muse Wonder ranked #7 overall with a composite score of 76.4.
• [01:29] Tweets from Meta Chief AI Officer Alexandr Wang and developer Theo discussing model training choices and whether 3D demos represent real code.
• [02:10] Split-screen visual comparison of 3D voxel sandbox scenes generated by Claude Opus 5.5 versus Meta Muse Wonder.
• [02:56] Interactive lawnmower driving demo comparing Opus 5.5 ($90.43) and Muse Wonder Full ($4.11).
• [03:30] Web 3D product visualizer generation test (headphones vs. sneaker).
• [05:22] Frontend interactive instructional UI generation (“Mohs scale of hardness” / rock identification) comparing Muse Wonder Full Max to Claude Fable 5.1 Max.
• [07:18] Meta’s official agency workflow demos (medical billing dispute review, running plan scheduling, and Instagram photo extraction for t-shirt design).
• [07:59] Muse Wonder pricing interface showing token rates and 1M context window options.
• [08:33] Artificial Analysis token efficiency chart comparing output tokens per task across leading models.
• [11:41] Interactive 3D Koi pond test comparing Muse Wonder Max against SWE 2 Max.
• [12:43] “Pocket Pop” handheld console landing page generation test.
• [13:11] Hands-on test of a browser-based macOS desktop clone complete with functional calculator, terminal, and audio player apps.
• [14:19] Hands-on test of “Wildhold”, a Three.js voxel survival game clone generated by Muse Wonder Full.
• [15:06] Hands-on test of “Deadlight House”, a Call of Duty Zombies-style browser game generated by the model.

Claims & numbers

• The presenter states that Muse Wonder ranks #7 overall on the World of AI benchmark leaderboard with a rating of 76.4.
• The presenter notes that on the Artificial Analysis Intelligence Index, Meta claims Muse Wonder Full ranks second with a score of 56, trailing Claude Opus 5.5 (58).
• Meta claims a score of 79 on the DeepSWE benchmark for Muse Wonder.
• The presenter shows that Muse Wonder API pricing is set at $4.00 per million input tokens ($0.20 cached input) and $20.00 per million output tokens, supporting a 1M token context window.
• The presenter reports that he exhausted his monthly quota on a $50 plan after running only three complex coding tests in MuseCode.
• In the 3D koi pond comparison, the presenter states Muse Wonder Max required 24 minutes and cost roughly $18 in compute, while SWE 2 Max generated a superior visual output in 15 minutes for free.
• The presenter shows a post from Alexandr Wang conceding: “it’s not as good as opus 5.5 on coding for sure, but also there’s a bunch of bugs right now that we’re looking into”.

Notable quotes

• “To start things off: No. This model is nowhere near Fable, regardless of what Zuckerberg or the Meta team claims.” [00:01]
• “Whole team feels dumb now, but it’s true, we did not explicitly train our model on 3D demo games...” [01:30] (quoting Alexandr Wang)
• “On paper, the benchmarks look incredible... but from what I’ve tested, there is still a massive gap between its benchmark performance and actual coding capabilities.” [15:42]

Assessment
This is an independent creator review and hands-on stress test evaluating Meta’s Muse Wonder release across practical coding, frontend development, and 3D web generation tasks. The presenter runs live outputs and side-by-side comparisons to substantiate his argument that the model trails top competitors despite favorable official benchmarks.

Described by gemini-3.8-flash on 2026-10-13 from the video’s audio and frames.