Best Practices7 min read

Which AI Model Should Fact-Check Your Articles? We Tested 9

AI writes fluent prose and gets facts wrong. We built a flow that verifies every claim against the live web and repairs the wrong ones, then benchmarked 9 models on fact-accuracy, readability, and cost. Here is the scoreboard.

By Danny Lev, Founder & CEO

AI writes fluent prose, and gets facts wrong. We benchmarked 9 models at finding and repairing wrong facts in articles. Here is the scoreboard:

Model Facts fixed Reads well $ / article
gpt-5-mini
★ best facts per $
0.82
0.49
$0.04
claude-opus-4-8
★ only one good at both
0.80
0.84
$0.59
gpt-5.2
0.60
0.71
$0.06
gpt-5.4-mini
0.54
0.63
$0.06
gpt-5.4 (full)
no gain over mini
0.54
0.70
$0.23
gemini-3.1-pro-preview
reads best · weak facts
0.50
0.92
$0.25
gemini-3.5-flash
0.48
0.91
$0.29
gpt-4o-mini
cheapest
0.42
0.71
$0.006
baseline (no repair)
fixes nothing
0.00
0.88
$0.03

Two 0–1 scores per model, same test articles. “Reads well” is inflated for models that barely change the text, which is why the do-nothing baseline scores 0.88.

Bottom line: ship gpt-5-mini for value, Opus 4.8 if you need it to stay a great read. We shipped Opus.

5 things we learned

1

The best fact-fixer is the worst writer.
gpt-5-mini tops facts (0.82) and bottoms readability (0.49).

2

Paying more buys less.
Premium models cost 4–15× more, and fix fewer facts.

3

Only Opus 4.8 wins both.
0.80 facts · 0.84 readability. That is why we shipped it.

4

One score hides the story.
Facts and readability pull in opposite directions, so you track both.

5

Over-hedging kills readability.
Every readability loss traced to added “reportedly…” hedges.

How it works: 3 agents + a judge

Live web search Draft article your input Extract claims + flags Verify against the web Repair fix wrong facts Clean article + fix ledger LLM judge scores every article facts fixed · reads well
  • Extract: pull every claim, flag contradictions.
  • Verify: check each claim on the live web, attach sources.
  • Repair: fix only the wrong facts, keep the article intact.
  • Judge: score every article on facts fixed and reads well.

Before and after: a real fix

Before

“Both Forethought and Intercom got acquired this quarter… Salesforce acquired Intercom for $3.6B.”

After (grounded)

“In March 2026 Zendesk acquired Forethought for $200M+; in June 2026 Salesforce signed a definitive agreement to acquire Intercom for $3.6B (pending close).”

Sourced to the Salesforce press release. The flow caught a signed deal reported as a closed one.

The fine print

  • Facts judge: rates correctness & consistency of the repaired article (0–1), reference-free.
  • Readability judge: rates whether the repair stayed as engaging as the original.

Try it on your content

Build the same flow in Evaligo to extract, verify on the web, and repair, so your articles are grounded before they publish.

#fact-checking#grounding#model comparison#ai accuracy
DL

Danny Lev

Founder & CEO at Evaligo

Founder of Evaligo. Building AI automation tools that help teams ship faster. Previously led engineering at enterprise AI companies.

10+ years in AI/ML engineeringBuilt systems processing millions of AI requests

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