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Run: 2026-11-11-01M753P26GQN66PPV0KWD4DNHR
Run Details
Model:
Muse Ember (Reasoning, Max)
Test:
Dialogue tags
Scenario:
Write 200 words with 50% dialogue
Duration:
6.2s
Cost:
$0.002006
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 disguise while Bill studied the invitation through binoculars behind the hedge. The birthday house glittered with balloons, banners, and an unusually suspicious amount of cake. "We go in as clowns, grab the presents, and leave before anyone notices." Bill said. "I cannot be a clown. I fear balloons, clowns, and children who know magic." Molly rolled her eyes and pointed at the pile of wrapped boxes stacked by the door. "Then you carry the loot while I distract the parents with a fake cake." Bill whispered nervously. "What if they ask for a magic trick and we only know one?" She grinned and pulled a rubber chicken from her coat. "Then we do the chicken trick, which always works, surprisingly, every single time." Bill stared at the party poppers and whispered again. "Last time it failed and a toddler chased us screaming for pudding." Molly tapped the invitation and explained the plan in perfect detail. "We sneak in, stack presents on a trolley, and wheel them out innocently." Bill nodded slowly despite his obvious growing terror. "Fine, but I keep the biggest present then." Molly agreed, then both thieves advanced toward the house giggling very nervously together.
created_at
"2026-11-11T10:50:28.95Z"
11/11/2026, 10:50:28 AM
model
"meta/muse-ember-20261109"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1514
moderation_latency
(null)
generation_time
6154
tokens_prompt
75
tokens_completion
316
native_tokens_prompt
69
native_tokens_completion
3999
native_tokens_completion_images
0
native_tokens_reasoning
3723
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
0.0020064
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer
(null)
request_id
"req-1794394228-4iCQKEJfQ7MPCYeWt4VR"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1794394228-DkTCTr4GkaxerncZurv4"
upstream_id
"resp_6af448758fd5fd0241f24da6"
provider_responses
0
endpoint_id
"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id
"resp_6af448758fd5fd0241f24da6"
is_byok
false
latency
725
model_permaslug
"meta/muse-ember-20261109"
provider_name
"Meta"
status
200
total_cost
0.0020064
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%