Is Meta’s Muse Wonder model any good?

I put Meta’s new Muse Wonder (and Wonder Full) frontier models through the How I AI bench, which covers nearly 20 tasks across prototyping, agentic workflows, coding, writing, and creative work. I scored everything with an LLM-as-a-judge pass and my own voice notes, then pulled together the first-look results you see here. *What you’ll learn:* 1. Why Meta’s “personal and professional agent” framing mostly holds up, and where it doesn’t 2. What active focus mode actually does on long-running tasks, and whether it’s real 3. The three agentic tasks where Muse ranked first, and why those categories matter 4. What Muse’s design output actually looks like (it’s not good) 5. How it compares to Sonnet on voice assistant tasks 6. Where Muse lands on SVG and short-form video versus Opus 5.5, Astra, and Fable 7. Whether I’m actually putting Muse into any of my agent workflows *Brought to you by:* DX—Engineering intelligence for the AI era: https://getdx.com/howiai Jira AI SDLC—Get your tokens’ worth with Jira: https://jira.dev *In this episode, we cover:* (00:00) Intro and what Muse Wonder is (01:19) Meta's frontier capability claims (04:36) Muse code (06:06) Benchmark overview and how the How I AI bench works (07:51) Overall results and TL;DR verdict (11:53) Agentic tasks (13:36) Email writing and voice assistant performance (14:35) Where Muse falls short (18:28) SVG illustration results (19:33) Short-form video editing (21:18) Fast on one-shot work, slow on agent tasks (22:15) Final verdict and where I'll use Muse Wonder next *Tools referenced:* • Meta Muse Wonder / Muse Wonder Full: https://research.meta.ai/blog/muse-wonder • Muse Code: https://developer.meta.com/ai/lp/muse-code *Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo *Have a really cool use case of how you use AI in your work? Let us know:* https://docs.google.com/forms/d/e/1FAIpQLSfP8wYCeDo5K0DxscDmoqgkxYY8ngA3B2anUDDvC4xadGTerg/viewform _Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co._

Claire Vohost

Oct 14, 202624mWatch on YouTube ↗

EPISODE INFO

Released: October 14, 2026
Duration: 24m
Channel: How I AI
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

I put Meta’s new Muse Wonder (and Wonder Full) frontier models through the How I AI bench, which covers nearly 20 tasks across prototyping, agentic workflows, coding, writing, and creative work. I scored everything with an LLM-as-a-judge pass and my own voice notes, then pulled together the first-look results you see here. *What you’ll learn:*
Why Meta’s “personal and professional agent” framing mostly holds up, and where it doesn’t
What active focus mode actually does on long-running tasks, and whether it’s real
The three agentic tasks where Muse ranked first, and why those categories matter
What Muse’s design output actually looks like (it’s not good)
How it compares to Sonnet on voice assistant tasks
Where Muse lands on SVG and short-form video versus Opus 5.5, Astra, and Fable
Whether I’m actually putting Muse into any of my agent workflows
*Brought to you by:* DX—Engineering intelligence for the AI era: https://getdx.com/howiai Jira AI SDLC—Get your tokens’ worth with Jira: https://jira.dev *In this episode, we cover:* (00:00) Intro and what Muse Wonder is (01:19) Meta's frontier capability claims (04:36) Muse code (06:06) Benchmark overview and how the How I AI bench works (07:51) Overall results and TL;DR verdict (11:53) Agentic tasks (13:36) Email writing and voice assistant performance (14:35) Where Muse falls short (18:28) SVG illustration results (19:33) Short-form video editing (21:18) Fast on one-shot work, slow on agent tasks (22:15) Final verdict and where I'll use Muse Wonder next *Tools referenced:*
Meta Muse Wonder / Muse Wonder Full: https://research.meta.ai/blog/muse-wonder
Muse Code: https://developer.meta.com/ai/lp/muse-code
*Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo *Have a really cool use case of how you use AI in your work? Let us know:* https://docs.google.com/forms/d/e/1FAIpQLSfP8wYCeDo5K0DxscDmoqgkxYY8ngA3B2anUDDvC4xadGTerg/viewform _Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co._

SPEAKERS

Claire Vo
host
Product leader and AI-focused creator, host of the podcast/YouTube channel “How I AI.”

EPISODE SUMMARY

In this episode of How I AI, featuring Claire Vo, Is Meta’s Muse Wonder model any good? explores muse Wonder excels as an agent, but lags in creative design Claire Vo benchmarks Meta’s Muse Wonder (and Wonder Full) against her “How I AI” task suite to test Meta’s frontier claims in agentic work, knowledge work, and coding.

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