Muse Spark 1.3 vs Muse Glimmer 30B vs Llama 4 Maverick vs Llama 4 Scout on people mentioned to a json array
Meta models side by side on "People mentioned to a JSON array": Llama 4 Scout scores 9/10; Llama 4 Scout is the cheapest answer scoring 8+ at $0.04 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.
Muse Spark 1.3
meta/muse-spark-1.3
1/10
Latency
2.0s
Cost
$0.00201
Per 1,000
$2.01
154 in · 428 out (353 reasoning) · 6 words · checks 2/6
✕json_valid
✓regex
✓contains
✕contains
✕contains
✕regex
[{"name":"Dana Okafor","role":"Head of Platform","email":"[email protected]"},{"name":"Luis Ferreira","role":"staff engineer","email":"luis
Judge: Output is incomplete/truncated and does not form valid JSON; the third person (Mei Tanaka) is missing entirely.
Muse Glimmer 30B
meta/muse-glimmer-30b
9/10
Latency
181ms
Cost
$0.00032
Per 1,000
$0.32
156 in · 251 out (158 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'.
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'.
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, Llama 4 Scout at $0.04 per 1,000 runs. If you need the top score, Llama 4 Scout at $0.04 per 1,000 runs.
If our calculators helped you cut down on hidden AI wallet leaks, thanks for using them. A tiny fraction of your savings is what keeps our pricing indexes updated daily.
Not sure which AI is cheapest for your use case? Find out in 30 seconds — no signup required.