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Run: 2026-09-03-01M1K5DX7895CRPABKXV2DZW0A
Run Details
Model:
Muse Spark 1.3 (Reasoning, Medium)
Test:
Dialogue tags
Scenario:
Write 200 words with 90% dialogue
Duration:
1m 8s
Cost:
$0.022278
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 90% 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
"Okay, the party starts at three, so we sneak in dressed as clowns with baggy pants for loot." said Molly. "I hate clowns, Molly. Last time the nose squeaked and that little kid bit my leg really hard." said Bill. "Stop whining. You distract the magician with your terrible balloon animals while I grab the present table." said Molly. "What if the parents catch us? There will be twenty moms filming everything on their phones, you know." said Bill. "They will be too busy arguing about gluten and juice boxes to notice two extra clowns stealing gifts." said Molly. "Fair point. The presents are for a seven year old. How much Lego and slime can we pawn?" said Bill. "Are you kidding? Last birthday haul got us four game consoles, three tablets, and a golden scooter, dummy." said Molly. "Okay, I am in. I will park the van by the castle and keep it running for getaway." said Bill. "Perfect. And remember the code word is sprinkles. You yell sprinkles if a kid starts crying or recognizes you." said Molly. "Got it. Sprinkles means run. Honestly stealing candy from babies was easier than robbing these spoiled birthday brats." said Bill.
created_at
"2026-09-03T08:16:09.966Z"
9/3/2026, 8:16:09 AM
model
"meta/muse-spark-1.3-20260902"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
3941
moderation_latency
(null)
generation_time
68050
tokens_prompt
75
tokens_completion
304
native_tokens_prompt
68
native_tokens_completion
5222
native_tokens_completion_images
0
native_tokens_reasoning
4932
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
"auto"
usage
0.0222785
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788423369-Lkwxl0gmPYg63YvV7qdq"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788423369-tXSqkMBi5RJoxGnxDrms"
upstream_id
"resp_6a992cca9553863d6ed04126"
provider_responses
0
endpoint_id
"cf4f1b4e-1719-4b65-9111-7dd7635e5a2f"
id
"resp_6a992cca9553863d6ed04126"
is_byok
false
latency
770
model_permaslug
"meta/muse-spark-1.3-20260902"
provider_name
"Meta"
status
200
total_cost
0.0222785
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: 90.00%, Deviation: 0.00%
neededClean
false
wordsTotal
200
wordsDialogue
180
100.0000%