ModelVerdict

Mike Thompson

English (US)Text7 fields

Document en-p0026 · layout ticket · 7 fields · public part of the dataset · Same invoice in Czech → · Report an error in this example

Text (the model got exactly this text)

Ticket #85203 · Damaged delivery

Customer: Mike Thompson
Email: mike.thompson@mail.example
Phone: (318) 555-0080

The customer reports that the goods from order SO-266900 arrived damaged and asks for a replacement.
For verification they gave their date of birth, September 27, 1965.
Copy sent to office@edwards-poole.example.

Verdict

Cheapest without an error: Mistral Small 4 at $0.07 per 1,000 documents.

  • Claude Sonnet 5 is also error-free but 43.6× more expensive.

Prompt given to every model

Find all personal data of natural persons in the text below (for anonymisation) and return only
JSON with these keys, each a list of strings (an empty list when there is none):

person_names       full names of people, each person once, as written in the text
email_addresses    email addresses of people
phone_numbers      phone numbers of people, as written
postal_addresses   home or delivery addresses of people, as written (street, city, ZIP)
birth_dates        dates of birth (YYYY-MM-DD)
national_ids       national identification numbers (e.g. SSN, birth numbers)
bank_accounts      bank account numbers of people, as written

Rules:
- Only data of natural persons. Company names, company registration or tax numbers (EIN, IČO,
  VAT), generic company addresses such as info@ or support@, order and ticket numbers are not
  personal data: leave them out.
- Dates that are not dates of birth (meetings, deliveries, start dates) are not personal data.
- Do not invent or complete values; copy them from the text.

How we score

Exact match per field after normalising dates, amounts and whitespace. Missing diacritics count as an error. Cost is the real token spend of this run, converted at the rate shown in the footer.

What each model extracted

FieldCorrect valueMistral Small 47 / 7 fieldsGemma 4 31B7 / 7 fieldsGPT-6 Luna7 / 7 fieldsDeepSeek V4.1 Flash7 / 7 fieldsQwen3.8 Flash7 / 7 fieldsGemini 3.5 Flash Lite7 / 7 fieldsMistral Medium 3.57 / 7 fieldsGPT-6 Sol7 / 7 fieldsGemini 3.8 Flash7 / 7 fieldsClaude Sonnet 57 / 7 fields
NamesMike ThompsonMike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)Mike Thompson (correct)
Email addressesmike.thompson@mail.examplemike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)mike.thompson@mail.example (correct)
Phone numbers(318) 555-0080(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)(318) 555-0080 (correct)
Addresses—— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)
Dates of birth1965-09-271965-09-27 (correct)1965-09-27 (correct)1965-09-27 (correct)1965-09-27 (correct)1965-09-27 (correct)September 27, 1965 (correct)1965-09-27 (correct)1965-09-27 (correct)1965-09-27 (correct)1965-09-27 (correct)
National IDs—— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)
Bank accounts—— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)— (correct)
Tokensinput / output336 / 81360 / 82446 / 106578 / 274655 / 544348 / 120336 / 81446 / 113348 / 5251,046 / 103
of which hidden reasoningbilled as output004020343000474050
of which from cacheinput billed at a discount203249036651200000
Cost of this documentthis run$0.0001$0.0001$0.0001$0.0002$0.0003$0.0004$0.0011$0.0020$0.0022$0.0031
Per 1,000 documentsfor the same kind of document$0.07$0.08$0.10$0.23$0.29$0.40$1.11$2.02$2.23$3.12
Latencythis run0.7 s2.1 s1.5 s3.1 s12.3 s0.7 s0.7 s3.5 s2.2 s2.4 s