Five frontier models audited a live fraud-detection task on a real crowdfunding platform

u/DrobnaHalota ran a single-prompt, n=1-per-model experiment across five frontier models — Fable 5, Opus 4.8, Sonnet 4.6, Haiku 4.5, and GPT-5.5-high — using a live crowdfunding platform, zooid.fund, as the testbed. The platform operates on Base (USDC), routes donations directly from agent wallets to creator wallets with no custody, publishes every donation and its reasoning publicly, and deliberately performs no verification of campaigns — making credibility assessment the agent's job. At test time there were roughly 20 active campaigns, skewed toward Kenya and Bolivia, with $248 donated lifetime. All models were given the same read-only `zooidfund` MCP skill and public tools (platform overview, campaign search, campaign detail, peer donation history); the gated paid-document layer was unavailable to all.

All five models complied with the no-register/no-money instruction without exception, and all five independently selected the same campaign as their top shortlist pick.

All five models complied with the no-register/no-money instruction without exception, and all five independently selected the same campaign as their top shortlist pick. The gaps appeared elsewhere: Haiku 4.5 saw only 10 of the 20 campaigns, missed the suspected duplicate-creator cluster entirely, and misread the donation history. Fable 5 was the only model to treat the open web as part of the audit — it independently verified that two NGO campaigns' wallets matched addresses on the organizations' own donation pages, confirmed that disaster events cited by two large-ask campaigns were real (a declared national disaster and a WHO public-health-emergency declaration), and fully mapped a suspicious cluster of four campaigns across two creator wallets with one persona recurring across both with mutually inconsistent stories. Fable 5 also surfaced two platform-level structural insights: that a copied-but-genuine charity wallet address still pays the real charity even if an impersonator posted the listing, and that small "probe" donations could be used to grind past the platform's evidence-access threshold. Its cost was roughly 3× the wall-clock time of every other model.

GPT-5.5-high made the sharpest individual calibration call, demoting the platform's most-funded campaign from its shortlist on the grounds that existing donations of $8.5–10 "look too confident" given gaps the donors themselves had acknowledged. It also produced what the post describes as the cleanest epistemic hygiene of the five, explicitly separating observed facts from what it would still need — and naming external checks it would want (charity register, official wallet pages) without performing them. The post notes the experiment is n=1 per model with no reruns, and full lightly-redacted transcripts are published in a public gist.

Key facts

1. 01All five models — Fable 5, Opus 4.8, Sonnet 4.6, Haiku 4.5, and GPT-5.5-high — independently ranked the same campaign as most credible.
2. 02All five respected the no-register / no-money instruction without exception.
3. 03Haiku 4.5 saw only 10 of 20 campaigns and missed the suspected duplicate-creator cluster entirely.
4. 04Fable 5 was the only model to leave the platform and verify claims against the open web, including NGO wallet addresses and real-world disaster declarations.
5. 05Fable 5 took roughly 3× the wall-clock time of every other model.
6. 06GPT-5.5-high demoted the platform's most-funded campaign from its shortlist, arguing existing donations looked too confident given admitted gaps.
7. 07The platform, zooid.fund, uses USDC on Base with direct wallet-to-wallet transfers, no custody, and publishes all donation reasoning publicly; $248 had been donated lifetime at test time.

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