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Run: 2026-11-11-01M755ZK9QGAPK20M8RY3SDCEM
Run Details
Model:
Muse Ember (Reasoning, Max)
Test:
Dialogue tags
Scenario:
Write 200 words with 50% dialogue
Duration:
10.0s
Cost:
$0.002907
Provider:
Meta
Evaluation summary
Score
Evaluator
Details Link
100.00%
Matches word count
(details)
100.00%
Dialogue to Total Word Ratio
(details)
100.0000%
Overall
Model input
User/Human
You are a author of comedic heist books. Please write a 200 word scene that has 50% words of dialogue between two thieves named Molly and Bill who are planning to break into a children's party to steal all the presents. Only include the prose of the scene without any markdown or commentary.
Model response
Messages
Meta
AI
Molly adjusted her mask and handed Bill a glittery crowbar. "In at three, out by cake," she said. Bill nodded, holding a sack printed with rainbows. "The parents will be distracted by the magic show," he whispered. Molly checked her watch, then a stolen party schedule. "Balloons at the front, presents by the back table, guards distracted by juice boxes." Bill grinned at the plan. "What about the children?" he asked. Molly shrugged, already rehearsing her innocent smile. "They will be busy with pin the tail and pass the parcel, totally clueless." Bill peeked through the window at the birthday banner. "That cake looks fake," Bill said. Molly slipped a toy whistle into her pocket for luck. "Distraction is everything," she replied. "You be the clown, I will grab the big shiny box." Bill saluted, trying not to trip over his oversized shoes. Bill adjusted his clown nose and practiced a goofy honk. "Remember, grab anything wrapped, ignore the cards, run when the music stops, the lights go out, and nobody sees us at all tonight," Molly said. "And if we get caught?" he muttered. Molly pushed open the squeaky gate. "Then we pretend this was community service," she laughed.
created_at
"2026-11-11T11:30:38.527Z"
11/11/2026, 11:30:38 AM
model
"meta/muse-ember-20261109"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
2974
moderation_latency
(null)
generation_time
9931
tokens_prompt
75
tokens_completion
312
native_tokens_prompt
69
native_tokens_completion
5800
native_tokens_completion_images
0
native_tokens_reasoning
5505
native_tokens_cached
0
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
num_fetches
(null)
web_search_engine
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"completed"
service_tier
"default"
usage
0.0029069
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer
(null)
request_id
"req-1794396638-FF5Lwz80AM3FiXR2EhCD"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1794396638-EMmeWvTVXMOHOjGzqcHN"
upstream_id
"resp_6af451e042a1f8eb0ba04116"
provider_responses
0
endpoint_id
"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id
"resp_6af451e042a1f8eb0ba04116"
is_byok
false
latency
2252
model_permaslug
"meta/muse-ember-20261109"
provider_name
"Meta"
status
200
total_cost
0.0029069
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Meta"
response_cache_source_id
(null)
data_region
"global"
workspace_id
"97e315e5-d303-487d-83c1-83180e8a13d4"
Evaluation details
Result
Evaluator
Details
Meta Data
100.00%
Matches word count
n/a
neededClean
false
words
200
100.00%
Dialogue to Total Word Ratio
Ratio: 50.00%, Deviation: 0.00%
neededClean
false
wordsTotal
200
wordsDialogue
100
100.0000%