Classify · 6 checks · max 400 tokens · benched 2026-11-05
Meta models side by side on "Label six support tickets": 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.
System
You are a classifier. Use only the allowed labels. Reply with JSON only, no prose, no code fences.
User
Classify each ticket into exactly one label from this set: billing, bug, feature_request, account_access. Return a JSON object mapping ticket id to label. t1: "I was invoiced for 12 seats but we only use 8." t2: "The export button does nothing when the report has more than 1,000 rows." t3: "Every time I open the dashboard on Safari the charts render blank." t4: "It would be great if we could schedule reports to email weekly." t5: "I reset my password twice and still cannot log in; it says my account is locked." t6: "Can you add a dark mode to the mobile app?"
Rubric for the judge: All six tickets get the right label from the fixed set, returned as a compact JSON object with no commentary.
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.
meta/muse-spark-1.3
190 in · 306 out (251 reasoning) · 12 words · checks 6/6
{"t1": "billing", "t2": "bug", "t3": "bug", "t4": "feature_request", "t5": "account_access", "t6": "feature_request"}Judge: All six tickets are correctly classified into the specified label set with proper JSON formatting and no extraneous commentary.
meta/muse-glimmer-30b
192 in · 183 out (143 reasoning) · 12 words · checks 6/6
{"t1": "billing", "t2": "bug", "t3": "bug", "t4": "feature_request", "t5": "account_access", "t6": "feature_request"}Judge: All six tickets are correctly classified into the specified label set with proper JSON formatting and no extraneous commentary.
meta-llama/llama-4-maverick
180 in · 46 out · 12 words · checks 6/6
{"t1": "billing", "t2": "bug", "t3": "bug", "t4": "feature_request", "t5": "account_access", "t6": "feature_request"}Judge: All six tickets are correctly classified into the specified label set with proper JSON formatting and no extraneous commentary.
meta-llama/llama-4-scout
180 in · 56 out · 16 words · checks 6/6
```
{
"t1": "billing",
"t2": "bug",
"t3": "bug",
"t4": "feature_request",
"t5": "account_access",
"t6": "feature_request"
}
```Judge: All six tickets are correctly classified into the appropriate labels from the fixed set, returned as a compact JSON object with no extra commentary.
Classify: All six tickets get the right label from the fixed set, returned as a compact JSON object with no commentary. The deterministic checks are json_valid, regex, regex, regex, regex, regex.
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.
Run it yourself
Re-run this prompt on Meta with your own OpenRouter key, or tweak the wording and see what changes.
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