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Run: 2026-11-11-01M753RDW9WMVB0RKQMHDVQ41X
Run Details
Model:
Muse Ember (Reasoning, Max)
Test:
Dialogue tags
Scenario:
Write 500 words with 70% dialogue
Duration:
9.7s
Cost:
$0.003783
Provider:
Meta
Evaluation summary
Score
Evaluator
Details Link
100.00%
Matches word count
(details)
99.37%
Dialogue to Total Word Ratio
(details)
99.6846%
Overall
Model input
User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 70% 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 stared at the party through binoculars shaped like flamingos while Bill rehearsed his evil laugh in the passenger seat. "Okay, Operation Birthday Bandit is officially a go," she announced. Bill replied, "First we distract the parents with my legendary balloon animal skills," Molly said, "You don't have skills, Bill, you have one deflated giraffe and a lawsuit from a clown college." Bill grinned, "Perfect, nobody will notice when we swap the real presents for my expired coupons." Molly whispered, "We need a code word for when Brenda the mommy blogger starts filming us for her vlog." Bill said, "If she films, I'll just do the worm and claim we're hired entertainment." Molly said, "You tried that at the library and they called security plus a priest." Bill said, "The priest was impressed by my commitment to the bit, though." Outside, children chased a piƱata shaped like a unicorn while a dad manned the grill wearing an apron that read King of Burgers. Molly said, "Rule one, we don't touch the cake because last time you ate the evidence." Bill said, "Rule two, if anyone asks our age, we say we're twins celebrating our twenty-first together." Molly said, "Bill, you are forty-three and you cried during the opening credits of Shrek." Bill said, "Shrek taught me about love, Molly, and also about ogres stealing princesses." Molly said, "Fine, but we are not stealing the bouncy castle again, it cost us three hours and a tow truck." Bill said, "Agreed, we stick to presents, preferably the big shiny ones that look expensive in photos." Molly said, "I counted forty-seven gifts on that table, which means forty-seven new toys for my nephew if we win." Bill said, "Your nephew is twenty-six and owns a kayak, Molly, he does not need a plastic dinosaur." Molly said, "He will love it emotionally, Bill, stop ruining the fantasy with your facts." A balloon popped near the fence and both thieves ducked dramatically behind a cooler full of juice boxes. Bill said, "We move at three, when the parents are busy watching the magician pull a rabbit from a hat." Molly said, "You mean the magician who is actually your cousin Steve in a cape?" Bill said, "Steve has range, Molly, last week he made a pigeon disappear at a wedding." Molly said, "Steve made the best man's wallet disappear and now he's banned from three venues." Bill said, "Details, details, we just need to grab and go before the singing starts." Molly checked her watch and then checked the gift table again through the flamingo binoculars. Molly said, "Alright, if this works, we split everything fifty-fifty and buy matching jackets." Bill said, "And if it fails, we blame the clown college and run toward the sprinklers." Molly said, "On three, we become best absolute legends of this whole neighborhood, partner, deal?" Bill nodded solemnly, tightened his clown nose, and pointed toward the presents as the magician finally pulled a rubber chicken from his sleeve instead.
created_at
"2026-11-11T10:51:46.449Z"
11/11/2026, 10:51:46 AM
model
"meta/muse-ember-20261109"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1130
moderation_latency
(null)
generation_time
9694
tokens_prompt
75
tokens_completion
936
native_tokens_prompt
69
native_tokens_completion
7552
native_tokens_completion_images
0
native_tokens_reasoning
6741
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
0.0037829
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer
(null)
request_id
"req-1794394306-1kEIsGo4QphkwzKF8awS"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1794394306-lDfT94gCgrd2Rq3H6EO6"
upstream_id
"resp_6af448c258e7883c5d774ee6"
provider_responses
0
endpoint_id
"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id
"resp_6af448c258e7883c5d774ee6"
is_byok
false
latency
1128
model_permaslug
"meta/muse-ember-20261109"
provider_name
"Meta"
status
200
total_cost
0.0037829
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
500
99.37%
Dialogue to Total Word Ratio
Ratio: 70.36%, Deviation: 0.36%
neededClean
false
wordsTotal
506
wordsDialogue
356
99.6846%