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Run: 2026-11-11-01M754HGSZ4AC93RHX1TQWVDE3
Run Details
Model:
Muse Ember (Reasoning, Max)
Test:
Dialogue tags
Scenario:
Write 200 words with 50% dialogue
Duration:
10.0s
Cost:
$0.003397
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 crouched behind a hedge outside Number Nine in a balaclava, a tutu, and absolutely no shame whatsoever. Molly whispered, "Bill, the coast is clear, but the bouncy castle guy is eating cake like it's a hostage negotiator during a very serious negotiation, honestly." Bill adjusted his scrunchie moustache and nodded seriously at the pink balloons bobbing gently overhead. Bill hissed, "Perfect. We distract the adults with my amazing karaoke, then snatch every present before the magician returns and notices anything missing at all." Molly checked her watch, which ticked loudly enough to wake neighbours and possibly the increasingly suspicious birthday boy. Molly said, "Your karaoke got us banned from a wedding, a funeral, and one very confused library." Bill grinned proudly, producing a coat-hanger grappling hook from nowhere at all. Bill replied, "Then tonight, Molly, we finally use my skills for good. Or at least for toys and expensive chocolate." On cue, the backyard door swung open and thirty children screamed in delight as a mountain of wrapped presents appeared. Molly whispered, "On three, we tiptoe in, grab everything shiny, and run like very naughty elves." Bill took a deep breath and whispered, "One, two, three. Huzzah for presents!"
created_at
"2026-11-11T11:05:28.652Z"
11/11/2026, 11:05:28 AM
model
"meta/muse-ember-20261109"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1523
moderation_latency
(null)
generation_time
10011
tokens_prompt
75
tokens_completion
336
native_tokens_prompt
69
native_tokens_completion
6780
native_tokens_completion_images
0
native_tokens_reasoning
6483
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
0.0033969
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer
(null)
request_id
"req-1794395128-S9wB9MryvCvYs6BDhPfJ"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1794395128-Vr5RWvUkPcDGkxqhiyTp"
upstream_id
"resp_6af44bf9bf432c9efe92420a"
provider_responses
0
endpoint_id
"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id
"resp_6af44bf9bf432c9efe92420a"
is_byok
false
latency
749
model_permaslug
"meta/muse-ember-20261109"
provider_name
"Meta"
status
200
total_cost
0.0033969
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: 49.75%, Deviation: 0.25%
neededClean
false
wordsTotal
201
wordsDialogue
100
100.0000%