Meta's Muse Wonder joins the board as the references move to policyengine-us 2.41.0
Meta's Muse Wonder joined the board on 2026-10-13, the day after Meta released it, bringing the board to 48 models. It is the first Meta model on the board. It gets 90.1% of answers within $1, weighted by household impact, #10 of 48. On the bounded score, which gives partial credit for amounts close to the reference, it ranks #3, behind only GPT-6 Sol and Claude Opus 5.5. GPT-6 Sol still leads on answers within $1 at 95.2%, ahead of Claude Opus 5.5 (94.1%) and GPT-5.6 Sol (93.1%).
Meta released Muse Wonder Full the same day, but only to Muse Code subscribers, with no API. PolicyBench runs every model through its provider's API under one protocol, so Muse Wonder Full is not on the board. PolicyBench reaches Muse Wonder through OpenRouter, whose one endpoint for it is Meta's own API. That API accepts only an automatic tool choice and rejects a forced tool call, so the row answers as a JSON object, as Claude Opus 5.5's and Claude Sonnet 5.5's do, and reasons at Meta's default setting.
The release also moves PolicyBench's references from policyengine-us 2.38.6 to 2.41.0, the first release with every fix the previous release was waiting on. Of the outputs the previous release excluded, nine return to scoring at the new version's values, each within $1 of the corrected value PolicyBench's audits computed for it. Between them they take the upstream fixes for Idaho's subtraction for health insurance premiums (policyengine-us #10023; two outputs), Wisconsin's retirement income exclusion before refundable credits and Wisconsin's capital gain subtraction for distributions (policyengine-us #10026; two outputs), the IRA deduction's active-participant phase-out, California's itemized deduction conformity and California's educator expense addback (policyengine-us #10032, #10034, #10052) and elective deferrals in the earned income behind the EITC and the refundable child tax credit (policyengine-us #10030; four outputs). The new version also fixes the defect behind a SNAP output, the heat-and-eat utility allowance, but that output stays excluded because the stated facts do not decide it. No reference PolicyBench already scored changes, and nothing is newly excluded. Every model is now scored on 1,935 of its 1,984 requested outputs; PolicyBench excludes the other 49.
Against the previous release, the exact rate of every one of the 47 earlier models falls, by 0.18 to 0.42 points. The cause is the nine restored outputs, which few models get right: half of them are answered within $1 by at most one of the 48 models, and four by none. Muse Wonder answers one of them within $1. Without them, every earlier model's rate would be the previous release's.