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Run: 2026-11-11-01M753R01E7502TVR9010KEDZB
Run Details
Model:
Muse Ember (Reasoning, Max)
Test:
Dialogue tags
Scenario:
Write 200 words with 10% dialogue
Duration:
12.2s
Cost:
$0.003448
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 10% 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 black balaclava while Bill tried to fit through the neighbor's dog door for the third time that evening. Their master plan to infiltrate Timmy's seventh birthday party required precision, patience, and absolutely no squeaky toy soldiers. "Tonight we enter through the laundry chute," Molly whispered. "And I will distract the clown," Bill promised. Bill had practiced his clown noises for weeks, which mostly sounded like a deflating balloon having an argument with a kazoo. "Perfect, steal all presents," Molly said. "Let's go," Bill said. Molly nodded solemnly and produced a tiny crowbar painted pink. They tiptoed across the damp garden toward a house glowing with balloons, banners, and what appeared to be an inflatable castle guarded by a very serious plastic flamingo. Inside, children shrieked with joy, adults chased runaway helium balloons, and the birthday boy prepared to make a wish that would probably involve dinosaurs eating the cake. Molly checked her watch, then her list, then her extremely illegal list of lists, because good heists always involved excellent paperwork and backup glitter glue. Bill whispered, "Ready," while Molly gripped the ladder, checked her pockets, and dramatically adjusted her cape for maximum sneaky effect in the moonlight.
created_at
"2026-11-11T10:51:32.276Z"
11/11/2026, 10:51:32 AM
model
"meta/muse-ember-20261109"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1549
moderation_latency
(null)
generation_time
12146
tokens_prompt
75
tokens_completion
339
native_tokens_prompt
69
native_tokens_completion
6883
native_tokens_completion_images
0
native_tokens_reasoning
6598
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
0.0034484
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer
(null)
request_id
"req-1794394292-YcB9m6TH0HSgvszA3sDo"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1794394292-3DWGBzSWTTiWbqyacAu3"
upstream_id
"resp_6af448b4d3da2088ef9c4214"
provider_responses
0
endpoint_id
"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id
"resp_6af448b4d3da2088ef9c4214"
is_byok
false
latency
642
model_permaslug
"meta/muse-ember-20261109"
provider_name
"Meta"
status
200
total_cost
0.0034484
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: 10.00%, Deviation: 0.00%
neededClean
false
wordsTotal
200
wordsDialogue
20
100.0000%