Meta's New Agent Models Rank Second to Claude Opus 5.5 and Undercut GPT-6 Astra

Meta has released Muse Wonder and Muse Wonder Full, two frontier models built for AI agents, the systems that carry out multi-step tasks on their own. On the Artificial Analysis leaderboard, Muse Wonder Full scores 55.8, just behind Claude Opus 5.5 at 57.6 and ahead of GPT-6 Astra. The base Muse Wonder runs a standard test workload for $0.80, the same as Claude Opus 5.5 and well under the $2 charged by GPT-6 Astra and Claude Fable 5.1. The numbers make Meta a serious contender, but they are not, on their own, a reason to drop the tools you already use.

What Meta released

Meta introduced the family in an announcement titled “Introducing Muse Wonder and Muse Wonder Full: Frontier Models for Agents,” which featured an introduction from Alexandr Wang. The release targets Anthropic’s Claude Opus 5.5 and Claude Fable 5.1 and OpenAI’s GPT-6 Astra directly.

• Muse Wonder is the standard model. It appears as Muse Wonder 1.0 in Meta’s web-based developer dashboard, where it sits alongside earlier models such as Muse Spark.
• Muse Wonder Full is the higher-performance flagship, built for complex enterprise agent work.

Both are available through Muse Code, Meta’s coding tool. In the developer dashboard, users can adjust temperature (how random the answers are), system instructions (standing directions given to the model), maximum output tokens, top-P, reasoning effort and search grounding.

Muse Code plans and limits

Muse Code is not a free consumer app. There is no standalone desktop or mobile app, and it requires a paid subscription. Developers install it from the terminal on macOS or Windows using the official install command. That setup may be a hurdle for people who are not used to working in a terminal.

The key detail: access to the flagship Muse Wonder Full is listed under the $50 Power Usage plan, so check the plan before counting on that model.

▲ Four Muse Code subscription tiers

What a standard workload costs

The cost comparison uses one workload sent directly to each model’s API: 100,000 uncached input tokens and 20,000 output tokens. Tokens are the small chunks of text that models read and write. The comparison is dated October 12, 2026.

Muse Wonder does the job for less than half the cost of GPT-6 Astra and Claude Fable 5.1. Against Claude Opus 5.5, though, it offers no price advantage, since both cost $0.80.

How the benchmarks line up

The Artificial Analysis leaderboard ranks the frontier models this way:

Muse Wonder Full trails Claude Opus 5.5 by 1.8 points but beats Claude Fable 5.1 and GPT-6 Astra. Even the base Muse Wonder lands within 0.3 points of GPT-6 Astra.

Coding results are stronger still. On Terminal-Bench 4.0-AA, DeepSWE 1.1, SWE-Marathon and ProgramBench, Muse Wonder Full matches or beats Claude Opus 5.5, Claude Fable 5.1 and GPT-6 Astra. Benchmarks are standardized tests that score models under the same conditions. For coding agent work in particular, these results suggest developers now have one more credible option at the top.

▲ Chasing new models versus mastering one

Before you switch

Master one model first

Jumping to every new release, canceling working subscriptions and starting over is often called shiny object syndrome. It tends to throw away the skill and results built up with the old setup. A better order is to learn one model thoroughly, use it to produce real results or income, and only then add others. One path looks like this: master Claude, add Codex later, try Gemini and drop it, and keep Claude and Codex side by side. Each model has its own personality and strengths, much like different friends, so it makes sense to match the model to the job.

Markets absorb new capabilities fast

The edge from a new model’s output does not last long. When ChatGPT first launched, AI-made marketing flyers felt new and impressive. Soon they were everywhere, and they lost their effect. Once people get used to a baseline level of output, only those using newer, more expensive models stand out, until that level becomes normal too. That fast absorption appears to be what drives the rapid pace of releases.

Prices may keep climbing

OpenAI already offers a $500-a-month plan, and Anthropic and Meta may follow with their own ultra-premium tiers. If the race continues at this pace, top-tier subscriptions could reach $1,500 to $2,000 a month by 2027. New frontier models could also keep arriving within weeks of each other. Paying for higher tiers only makes sense when real products, services, games or marketing assets bring in enough revenue to cover the cost.

The bottom line

Muse Wonder Full sits a narrow second to Claude Opus 5.5 overall and matches or leads it on several coding benchmarks. The base Muse Wonder costs the same as Claude Opus 5.5 for a standard workload and less than half as much as GPT-6 Astra. That makes Meta a strong new option, but not an automatic replacement for what already works.

If you want to try it, take these steps:

1. Write down the workflows and outputs that already work with your current model.
2. Give the same task, such as a code review or a marketing plan check, to Claude, GPT-6 Astra and Muse Code, and compare the answers.
3. Use the different answers as input, but keep the final decision yourself. Over-analyzing every response can slow you down.
4. If the new model does better, move your existing workflow onto it instead of rebuilding from scratch.
5. Upgrade to a pricier tier only when your revenue can cover it. If you need Muse Wonder Full, start by weighing the $50 Power Usage plan.