America.gov, the government's new assistant, scores level with GPT-5.5

America.gov, the General Services Administration's assistant, live since September 29, gets 87.9% of PolicyBench answers within $1, weighted by household impact. On the board it would rank #14 of 51, level with GPT-5.5 (87.9%); GPT-6 Sol leads at 95.2%. It does not join the board, which scores models answering alone, with no tools and no web access. America.gov says it uses "Super Intelligence (SI) to find and explain information from official government sources."

Between October 14 and 18, PolicyBench sent each of its 100 households to America.gov in a new chat, with the board's own prompt in the JSON answer format, and scored every reply as it scores the board. Six prompts run past the 8,000 characters America.gov asks a message to stay within, so each went in as two chats asking for half the outputs apiece. Before freezing a run, PolicyBench asks a board model again when its response leaves answers out, and America.gov got the same kind of retry: each refusal went back word for word in a fresh chat, up to twice. On first attempts alone it gets 86.6% (#19).

America.gov's first replies included five refusals. "I cannot estimate or calculate federal or state tax, credit, payroll, or benefit amounts," it replied to the prompt for a Virginia single parent of two. Asked again, two of the refusals turned into full answers and three came back word for word the same, which leaves 3.7% of its scored answers blank; 46 of the 50 models on the board answer every one.

America.gov is strongest on taxes. It gets 72.6% of federal income tax amounts within $1, against a median of 54.8% across the board's models, and 66.7% of state income tax amounts, against 60.2%. Benefits are weaker. On SNAP it gets 81.7%, below the median of 84.9%, and it put a Michigan couple's SNAP at $6,432 a year where the reference and 49 of the 50 models say $0. On Medicaid eligibility, the output that carries the most weight, it gets 92.5% against a median of 95.4%, and it called both adults in a New York couple eligible where the reference and 49 models say neither is.

The current prompts define four outputs by PolicyEngine: Medicaid and CHIP eligibility "under PolicyEngine rules," and the two school-meal outputs as whether "PolicyEngine returns" support. PolicyBench is revising that wording. At least two of America.gov's five refusals cited PolicyEngine; no model on the board declined a household on that ground, though some models' recorded reasoning notes that they cannot run PolicyEngine. Counting only the answers each gave, America.gov is never more than 0.8 points below the median model on those four outputs, and without them it would rank #13 of 51.

This is one run, from one week in October, and America.gov's terms say answers generated with SI "can be incomplete or wrong." The board's last repair step, asking again for each answer still missing, one at a time, would take at least 73 more chats and could lift America.gov to 89.8% at most. The replies, the scores and the method, including how the long prompts were split, are in the data below.