last updated 2026-10-19

TreasuryQA Bench

An agent benchmark for working an archive of scanned financial records. The agent gets one question and a cloud drive holding 1,435 scanned U.S. Treasury volumes with no text layer. It has to find the right volume, read the right page through a hosted OCR server, and reply with one exact figure. A script, not a model, decides whether that figure is right.

Leaderboard

Agentpass@1exact figure95% CIpass³all 3 repeatsClear26 tasksVery blurry20 tasksAnsweredcommitted a figureRight thenof those$/taskHarness · model idno aliases
Claude Opus 5.564.8%55.7–73.345.7%62%60%93.8%69.0%~$1.56Claude Code claude-opus-5-5
Gemini 4 Argon60.0%50.0–70.045.7%55%50%72.4%82.9%~$2.45Gemini CLI gemini-4-argon
GPT-6.1 Sol51.4%41.0–61.438.6%73%25%90.5%56.8%~$0.62Codex gpt-6.1-sol
Gemini 3.8 Flash51.0%40.5–61.437.1%55%37%84.3%60.5%~$1.74Gemini CLI gemini-3.8-flash
Claude Sonnet 5.541.9%31.9–51.927.1%54%12%89.0%47.1%~$1.19Claude Code claude-sonnet-5-5
DeepSeek V4.1 Flash37.1%28.1–46.217.1%40%20%84.3%44.1%~$0.25Pi DeepSeek-V4.1-Flash
Grok 4.718.1%11.4–25.24.3%21%3%80.5%22.5%~$3.55Grok CLI grok-4.7
GPT-5.6 Terra16.7%10.0–24.38.6%24%3%93.3%17.9%~$1.17Codex gpt-5.6-terra

Cost vs. questions answered correctly

10%20%30%40%50%60%70%$0.25$0.50$1.00$2.00$4.00agent-side cost per task (log scale)GPT-5.6 TerraGrok 4.7DeepSeek V4.1 FlashClaude Sonnet 5.5Gemini 3.8 FlashGPT-6.1 SolGemini 4 ArgonClaude Opus 5.5Claude Opus 5.5Gemini 4 ArgonGPT-6.1 SolGemini 3.8 FlashClaude Sonnet 5.5DeepSeek V4.1 FlashGrok 4.7GPT-5.6 Terra

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