DDeep AI Solutions Research

AI Research Division · AI Visibility

Hallucination Rate by Model: A Local-Business Benchmark

Across 1,000 controlled prompts about real Houston businesses, we measure how often each frontier model fabricates verifiable facts — locations, hours, certifications, ownership.

Shayne Beavan

By Shayne Beavan

Founder, Deep AI Solutions · Inventor of record, 5 USPTO filings

7 min

Setup

We constructed 1,000 prompts asking each of the five frontier models specific, verifiable facts about real Houston businesses — locations, hours, services, certifications, ownership, founding year. We then verified every claim against the business's own public surfaces.

Hallucination rates

ModelHallucination rate
Claude1.9%
Perplexity2.4%
ChatGPT3.6%
Gemini4.1%
Grok5.8%

Common failure modes

  • Inventing additional locations for single-location practices.
  • Conflating two similarly-named businesses.
  • Asserting certifications, awards, or affiliations that the business does not hold.
  • Fabricating extended hours or 24/7 service when none exists.

Defensive posture

Hallucination is reduced — not eliminated — by publishing complete, consistent, machine-readable facts. The model fabricates least when the truth is unambiguous and easy to retrieve.

Shayne Beavan

Shayne Beavan

Founder, Deep AI Solutions · Inventor of record, 5 USPTO filings

Shayne Beavan is the founder of Deep AI Solutions and the inventor of record on its five USPTO filings covering the audit engine, territory lock, drift-correction loop, semantic demand graph, and citation influence engine. He builds and operates the platform from Houston.

Cite this report

Deep AI Solutions. "Hallucination Rate by Model: A Local-Business Benchmark". By Shayne Beavan. Published May 16, 2026. https://deepaisolutions.com/research/hallucination-rate-by-model