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Extract JSON · 6 checks · max 400 tokens · benched 2026-09-16

Muse Spark 1.3 vs Muse Glimmer 30B vs Llama 4 Maverick vs Llama 4 Scout on invoice text to json

Meta models side by side on "Invoice text to JSON": Llama 4 Scout scores 10/10; Llama 4 Scout is the cheapest answer scoring 8+ at $0.03 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

Extract the fields below from the invoice text and return one JSON object with exactly these keys: vendor (string), invoice_number (string), total (number), currency (ISO 4217 string), due_date (YYYY-MM-DD string).

Invoice text:
Northwind Print Co.
Invoice INV-2041
Issued: 15 September 2026
Payment due: 15 October 2026
Items: 500 x A5 flyers @ 1.20 = 600.00; 4 x roll-up banners @ 171.13 = 684.50
Total due: USD 1,284.50
Thank you for your business.

Rubric for the judge: Valid JSON with the five keys, numeric total 1284.5, ISO due date, no extra keys or commentary.

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

unjudged
failed: OpenRouter HTTP 403: This model requires you to complete the following before use: 18+ age confirmation. Confirm at https://openrouter.ai/settings/preferences.
Latency
0ms
Cost
$0
Per 1,000
$0

0 in · 0 out · 0 words · checks 0/6

  • json_valid
  • json_keys
  • contains
  • contains
  • contains
  • contains
(empty output)

Judge:

Muse Glimmer 30B

meta/muse-glimmer-30b

10/10
Latency
154ms
Cost
$0.00018
Per 1,000
$0.18

181 in · 113 out (50 reasoning) · 12 words · checks 6/6

  • json_valid
  • json_keys
  • contains
  • contains
  • contains
  • contains
{"vendor": "Northwind Print Co.", "invoice_number": "INV-2041", "total": 1284.5, "currency": "USD", "due_date": "2026-10-15"}

Judge: Output is valid JSON with exactly the five required keys, correct numeric total (1284.5), proper ISO 4217 currency code (USD), correctly formatted due date (2026-10-15), no extra keys or commentary.

Llama 4 Maverick

meta-llama/llama-4-maverick

10/10
Latency
586ms
Cost
$6.7e-5
Per 1,000
$0.07

169 in · 47 out · 12 words · checks 6/6

  • json_valid
  • json_keys
  • contains
  • contains
  • contains
  • contains
{"vendor": "Northwind Print Co.", "invoice_number": "INV-2041", "total": 1284.50, "currency": "USD", "due_date": "2026-10-15"}

Judge: Output is valid JSON with exactly the five required keys, correct numeric total (1284.50), proper ISO 4217 currency code (USD), correctly formatted due date (2026-10-15), no extra keys or commentary.

Llama 4 Scout

meta-llama/llama-4-scout

10/10
top judge scorecheapest scoring 8+
Latency
6.3s
Cost
$3.4e-5
Per 1,000
$0.03

169 in · 56 out · 16 words · checks 6/6

  • json_valid
  • json_keys
  • contains
  • contains
  • contains
  • contains
```
{
  "vendor": "Northwind Print Co.",
  "invoice_number": "INV-2041",
  "total": 1284.50,
  "currency": "USD",
  "due_date": "2026-10-15"
}
```

Judge: All five required keys present with correct values: vendor, invoice_number, total as number 1284.50, currency as ISO 4217 code USD, and due_date in YYYY-MM-DD format; no extra keys or commentary.

Frequently asked

What does this prompt test?

Extract JSON: Valid JSON with the five keys, numeric total 1284.5, ISO due date, no extra keys or commentary. The deterministic checks are json_valid, json_keys, contains, contains, contains, contains.

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 $0.03 per 1,000 runs. If you need the top score, Llama 4 Scout at $0.03 per 1,000 runs.

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