# EP 06: Meta's Muse Wonder Remembers Everything. Your Other AIs Don't. - URL: https://www.agenticpod.net/episodes/ep06-muse-wonder-memory/ - Watch on YouTube: https://www.youtube.com/watch?v=qmroxPpFeiI - Published: 2026-10-12 - Length: 5 min - Hosts: Stella (asks), Liam (answers). Both are AI hosts with AI-generated voices. ## Summary Does Meta's Muse Wonder remember between conversations? Yes: its Active Memory carries context across chats, and it tops Meta's own MemoryBench. Liam and Stella end with the catch: that memory lives inside Meta's app only, unlike a shared layer like Vilix AI that follows you across every tool. ## Chapters - 0:00 Intro - 0:18 The launch and the scoreboard - 1:21 What Active Memory does - 1:51 No model wins every row - 2:45 One memory for every model - 3:54 Agencies and recap ## Resources - [Read the article](https://vilix.ai/blog/muse-wonder-active-memory-claude-chatgpt-codex/) - [Full technical guide (setup for Muse, Claude, ChatGPT, Codex, prompts, FAQ)](https://github.com/asly-97/ai-automation-workflows/tree/main/muse-wonder-memory) - [Vilix AI, one shared memory for ChatGPT, Claude, Claude Code, Codex, Cursor, OpenClaw, Hermes, Muse and every MCP tool](https://vilix.ai) - [Connect Vilix AI in under two minutes per tool](https://vilix.ai/get-started) ## Transcript ### Intro Liam: Hey hey hey, welcome to Agentic Pod! I'm Liam. Stella: And I'm Stella! And, you know, Meta just dropped Muse Wonder, and the big feature is memory. Like, it actually remembers you. Liam: Finally, someone in tech who remembers my name. Stella: Don't get attached. Okay, let's go. ### The launch and the scoreboard Stella: So what did Meta actually launch? Liam: Two models from Meta Superintelligence Labs, Muse Wonder and Muse Wonder Full. Wonder is the fast one, it's out now through the Meta Model API and Muse Code, and Full is on Muse Code's higher plans. Both have a 1 million token context window, and the API is about 4 dollars per million input tokens and 20 per million output. Stella: Okay, and I have the table, so let me read it, right? Meta's own MemoryBench. Muse Wonder, 85.6. Wonder Full, 85.5. Claude Opus 5.5, 81.5. GPT-6 Astra, 81.4. Liam: Mhm. Stella: So Meta made a memory test and Meta won the memory test. Liam: It's their benchmark, yeah, independent numbers are still coming in. But honestly the bigger news is that memory is a benchmark now. A year ago it was a side feature, and now labs put it on the launch slide. ### What Active Memory does Stella: Okay so what does Active Memory, like, actually do? Liam: It carries the important stuff across conversations and pulls it back in when it's relevant. So you mention your project on Monday, and on Thursday Muse just, uh, knows. And there's a second feature, Active Focus, which keeps the model going when a task gets hard, tries other approaches, and recovers from errors. Stella: Honestly I need Active Focus for my Mondays. Liam: Same, but they only ship it to models. ### No model wins every row Stella: So, so is Muse Wonder just the best now? Like, do I switch everything? Liam: That's the fun part, because even Meta's own table says no. Wonder Full leads legal work on Harvey LAB, AutomationBench, DeepSWE and SWE-Marathon. Claude Opus 5.5 still leads Terminal-Bench, ProgramBench and JobBench. And GPT-6 Astra leads GDP.pdf, the document work. Stella: Huh. So everybody wins something. Liam: Right? Everybody gets a trophy. So the smart setup is using the best model for each job. You plan in ChatGPT on your phone, you build in Claude Code or Codex, and you hand legal and finance research to an agent running Muse Wonder. Stella: Yeah, yeah. But wait, if I use three models, then... Liam: Then you've got three memories. ### One memory for every model Stella: Right, because Muse remembers what I told Muse, and Claude remembers what I told Claude, and they don't, like, talk. Liam: Exactly, each lab's memory lives in its own app. So every switch means re-briefing, the project, the decisions, the client's tone, what already failed. And the better each memory gets, the more you notice it doesn't follow you. Stella: Okay so how do I fix that? Liam: Vilix AI. It's one shared memory that every model reads over MCP. Before a reply, the tool calls get context, and Vilix AI hands back your relevant history, your rules and your open tasks. After the reply it calls save turn, and the exchange is saved with a source label, so you know it came from Muse or Claude or Codex. And when two tools disagree, the newest one wins. Stella: Oh, nice. And, like, my rules? Liam: User rules for your personal stuff, project rules for the stack and the tone, projects and tasks so every model sees what's open, and skills, so a procedure you build once gets followed by every agent. Plus the Vilix AI agent inbox, so you leave a note from your phone and your agents read it on their next run. And Muse is on the Vilix AI supported list too. ### Agencies and recap Stella: Okay, and agencies, you know, people building agents for clients? Liam: That's the big one. You give each client their own Vilix AI account, and every agent you build for them, on any model, is wired to that client's key. So when Muse Wonder wins a task you run for that client, you swap the model, and the client's whole history comes along. Stella: No re-briefing. I love it. Recap me. Liam: Muse Wonder brings real memory to Meta's models, and no single model wins every task. So use the best one for each job, and connect them all to Vilix AI so your context, rules, tasks and skills follow you between Muse, Claude, ChatGPT and Codex. The article, the setup guide and the Vilix AI links are in the description. See you next time. Stella: Bye!