GPT-5.5 vs GPT-5.4 vs GPT-5.4 mini vs GPT-5.4 Nano vs GPT-5.3-Codex on people mentioned to a json array
OpenAI models side by side on "People mentioned to a JSON array": GPT-5.4 Nano scores 9/10; GPT-5.4 Nano is the cheapest answer scoring 8+ at $0.15 per 1,000 runs. Outputs, checks, judge reasons, latency and cost.
The prompt every model received
System
You are a data extraction engine. Reply with JSON only, no prose, no code fences.
User
From the text, return a JSON array of every person mentioned. Each element is an object with keys name, role, email (use null when an email is not given). Preserve the order in which people first appear.
Text: The migration is led by Dana Okafor (Head of Platform, [email protected]). She is supported by Luis Ferreira, a staff engineer, whose address is [email protected]. Questions about billing go to Mei Tanaka, our finance lead; she prefers phone calls and has not shared an email.
Rubric for the judge: A three-element JSON array in order (Dana, Luis, Mei) with correct roles, emails and a JSON null for Mei.
Side by side
Every cell is one OpenRouter call at temperature 0 with the prompt's token cap and reasoning effort "low" where the model supports it. Cost is usage × the catalogue rate in models.json. Quality is one judge call to anthropic/claude-haiku-4.5 against the prompt's rubric, cached per prompt version.
GPT-5.5
openai/gpt-5.5
9/10
Latency
385ms
Cost
$0.00427
Per 1,000
$4.27
140 in · 119 out (16 reasoning) · 33 words · checks 6/6
Judge: Correct structure, order, and content with all three people and proper null handling, but 'staff engineer' and 'finance lead' lack capitalization consistency with 'Head of Platform'.
GPT-5.4
openai/gpt-5.4
9/10
Latency
553ms
Cost
$0.00147
Per 1,000
$1.47
140 in · 75 out (10 reasoning) · 8 words · checks 6/6
✓json_valid
✓regex
✓contains
✓contains
✓contains
✓regex
[{"name":"Dana Okafor","role":"Head of Platform","email":"[email protected]"},{"name":"Luis Ferreira","role":"staff engineer","email":"[email protected]"},{"name":"Mei Tanaka","role":"finance lead","email":null}]
Judge: Correct structure, order, and content with all three people and proper null for Mei's email, but 'staff engineer' and 'finance lead' lack capitalization consistency with 'Head of Platform'.
GPT-5.4 mini
openai/gpt-5.4-mini
9/10
Latency
411ms
Cost
$0.00059
Per 1,000
$0.59
140 in · 107 out (42 reasoning) · 8 words · checks 6/6
✓json_valid
✓regex
✓contains
✓contains
✓contains
✓regex
[{"name":"Dana Okafor","role":"Head of Platform","email":"[email protected]"},{"name":"Luis Ferreira","role":"staff engineer","email":"[email protected]"},{"name":"Mei Tanaka","role":"finance lead","email":null}]
Judge: Correct structure, order, and content with all three people and proper null for Mei's email, but 'staff engineer' and 'finance lead' lack capitalization consistency with 'Head of Platform'.
Judge: Correct structure, order, and content with all three people and proper null handling, but role capitalization differs slightly from source text (e.g., 'Staff Engineer' vs 'staff engineer').
GPT-5.3-Codex
openai/gpt-5.3-codex
9/10
Latency
426ms
Cost
$0.00212
Per 1,000
$2.12
140 in · 134 out (31 reasoning) · 33 words · checks 6/6
Judge: Correct structure, order, and content with all three people and proper null handling, but 'staff engineer' and 'finance lead' lack capitalization consistency with 'Head of Platform'.
Frequently asked
▸What does this prompt test?
Extract JSON: A three-element JSON array in order (Dana, Luis, Mei) with correct roles, emails and a JSON null for Mei. The deterministic checks are json_valid, regex, contains, contains, contains, regex.
▸Which model should I pick for this task?
If the judge's bar of 8/10 is good enough for you, GPT-5.4 Nano at $0.15 per 1,000 runs. If you need the top score, GPT-5.4 Nano at $0.15 per 1,000 runs.
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