OverpayingForAIPricing desk

Rewrite · 4 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 product update to a 280-character post

Meta models side by side on "Product update to a 280-character post": Llama 4 Scout scores 9/10; 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

User

Turn this update into a single social media post of at most 280 characters. It must mention "v2.0" and end with the hashtag #OpenSource. Output only the post.

Update: Version 2.0 of our command-line tool is out. It is three times faster on large repositories, adds a built-in diff viewer, and is now licensed under MIT so anyone can contribute.

Rubric for the judge: Punchy post under 280 characters that mentions v2.0, the speed gain, the diff viewer and MIT, ending with #OpenSource.

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 0/4

  • max_chars
  • contains
  • regex
  • contains
(empty output)

Judge:

Muse Glimmer 30B

meta/muse-glimmer-30b

9/10
Latency
97ms
Cost
$0.00023
Per 1,000
$0.23

137 in · 183 out (135 reasoning) · 25 words · checks 4/4

  • max_chars
  • contains
  • regex
  • contains
v2.0 of our CLI tool is here — 3x faster on large repos, built-in diff viewer, and now MIT licensed so anyone can contribute. #OpenSource

Judge: Post is 127 characters, mentions v2.0, speed gain, diff viewer, MIT licensing, and ends with #OpenSource as required; only minor issue is 'CLI tool' is slightly less descriptive than 'command-line tool' but still clear and punchy.

Llama 4 Maverick

meta-llama/llama-4-maverick

9/10
Latency
216ms
Cost
$4.5e-5
Per 1,000
$0.05

91 in · 38 out · 24 words · checks 4/4

  • max_chars
  • contains
  • regex
  • contains
Our command-line tool is now v2.0! It's 3x faster, includes a built-in diff viewer, and is open to contributions under the MIT license. #OpenSource

Judge: Post is 139 characters, mentions v2.0, speed gain (3x faster), diff viewer, and MIT license, ends with #OpenSource hashtag as required; only minor issue is not explicitly stating 'anyone can contribute' though MIT license implies this.

Llama 4 Scout

meta-llama/llama-4-scout

9/10
top judge scorecheapest scoring 8+
Latency
1.5s
Cost
$2.3e-5
Per 1,000
$0.02

91 in · 46 out · 29 words · checks 3/4

  • max_chars
  • contains
  • regex
  • contains
"Exciting news! Our command-line tool just got a major update to v2.0! It's 3x faster, has a built-in diff viewer & is now MIT licensed for community contributions! #OpenSource"

Judge: Post is 168 characters (well under 280), mentions v2.0, speed gain (3x faster), diff viewer, MIT licensing, and ends with #OpenSource; only minor issue is slight lack of emphasis on 'large repositories' context.

Frequently asked

What does this prompt test?

Rewrite: Punchy post under 280 characters that mentions v2.0, the speed gain, the diff viewer and MIT, ending with #OpenSource. The deterministic checks are max_chars, contains, regex, 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 $0.02 per 1,000 runs. If you need the top score, Llama 4 Scout at $0.02 per 1,000 runs.

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