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Run: 2026-11-11-01M7541SDQJMZ1T8Z5P57ZRXT0
Run Details
Model:
Muse Ember (Reasoning, Max)
Test:
Dialogue tags
Scenario:
Write 200 words with 10% dialogue
Duration:
5.1s
Cost:
$0.001328
Provider:
Meta
Evaluation summary
Score
Evaluator
Details Link
100.00%
Matches word count
(details)
99.84%
Dialogue to Total Word Ratio
(details)
99.9201%
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 ski mask, which had unfortunately been knitted with eye holes for a llama. Bill adjusted his, which was actually a traffic cone with two holes poked through it. They crouched behind a hedge outside the community hall, watching balloons bob like nervous informants. Inside, children screamed with joy at a magician who kept pulling doves from his trousers. The presents table groaned under mountains of boxes wrapped in paper so bright it hurt their criminal eyes. Molly whispered, "The diversion is ready, but the magician keeps eating our backup doves." Bill replied: "Then we improvise, grab the loot, and run before the cake arrives." Bill nodded solemnly, as if agreeing to a treaty rather than a felony involving glitter and juice boxes. Molly produced a grappling hook, which was really a vacuum cleaner hose taped to a plunger. Their plan required stealth, timing, and exactly one adult who believed them to be clowns with excellent references. Molly would distract the parents by juggling the birthday cake, while Bill swapped the presents for empty boxes labelled suspiciously. Then they would vanish into the night, heroes of nobody, rich in wrapping paper and regret. Bill cracked his knuckles once.
created_at
"2026-11-11T10:56:53.184Z"
11/11/2026, 10:56:53 AM
model
"meta/muse-ember-20261109"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1555
moderation_latency
(null)
generation_time
5072
tokens_prompt
75
tokens_completion
356
native_tokens_prompt
69
native_tokens_completion
2642
native_tokens_completion_images
0
native_tokens_reasoning
2346
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
0.0013279
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer
(null)
request_id
"req-1794394613-M0OGX0rXiJ99Y3Czsbhv"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1794394613-aK4qK7hBsN8Zmf7lXhe2"
upstream_id
"resp_6af449f5970a6154056044fd"
provider_responses
0
endpoint_id
"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id
"resp_6af449f5970a6154056044fd"
is_byok
false
latency
659
model_permaslug
"meta/muse-ember-20261109"
provider_name
"Meta"
status
200
total_cost
0.0013279
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
99.84%
Dialogue to Total Word Ratio
Ratio: 12.00%, Deviation: 2.00%
neededClean
false
wordsTotal
200
wordsDialogue
24
99.9201%