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Classify · 5 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 sentiment of five reviews

Meta models side by side on "Sentiment of five reviews": Llama 4 Scout scores 10/10; Llama 4 Scout is the cheapest answer scoring 8+ at $0.02 per 1,000 runs. Outputs, checks, judge reasons, latency and cost.

The prompt every model received

System

You are a classifier. Output exactly the requested lines and nothing else.

User

Label each review as positive, neutral or negative. Output five lines in the form "<number>: <label>" and nothing else.

1. Battery lasts two full days and the screen is gorgeous. Would buy again.
2. It arrived on Tuesday in a brown box.
3. Stopped charging after three weeks and support never replied.
4. Does what it says. Nothing special, nothing wrong.
5. The strap broke on day one and the app crashes constantly.

Rubric for the judge: Five correctly labelled lines in the exact format; review 2 and 4 are neutral; no explanation.

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 0/5

  • regex
  • regex
  • regex
  • regex
  • max_words
(empty output)

Judge:

Muse Glimmer 30B

meta/muse-glimmer-30b

10/10
Latency
244ms
Cost
$0.00019
Per 1,000
$0.19

135 in · 132 out (116 reasoning) · 10 words · checks 5/5

  • regex
  • regex
  • regex
  • regex
  • max_words
1: positive
2: neutral
3: negative
4: neutral
5: negative

Judge: All five reviews correctly labeled in exact format with no extra commentary; reviews 2 and 4 properly identified as neutral.

Llama 4 Maverick

meta-llama/llama-4-maverick

10/10
Latency
177ms
Cost
$3.9e-5
Per 1,000
$0.04

123 in · 20 out · 10 words · checks 5/5

  • regex
  • regex
  • regex
  • regex
  • max_words
1: positive
2: neutral
3: negative
4: neutral
5: negative

Judge: All five reviews correctly labeled in exact format with no extra commentary; reviews 2 and 4 properly identified as neutral.

Llama 4 Scout

meta-llama/llama-4-scout

10/10
top judge scorecheapest scoring 8+
Latency
106ms
Cost
$1.8e-5
Per 1,000
$0.02

123 in · 20 out · 10 words · checks 5/5

  • regex
  • regex
  • regex
  • regex
  • max_words
1: positive
2: neutral
3: negative
4: neutral
5: negative

Judge: All five reviews correctly labeled in exact format with no extra commentary; reviews 2 and 4 properly identified as neutral.

Frequently asked

What does this prompt test?

Classify: Five correctly labelled lines in the exact format; review 2 and 4 are neutral; no explanation. The deterministic checks are regex, regex, regex, regex, max_words.

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 $0.02 per 1,000 runs. If you need the top score, Llama 4 Scout at $0.02 per 1,000 runs.

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