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Run: 2026-09-03-01M1K5RPXPEJWNTBPGBBG988ME
Run Details
Model:
Muse Spark 1.3 (Reasoning, Medium)
Test:
Dialogue tags
Scenario:
Write 200 words with 90% dialogue
Duration:
1m 32s
Cost:
$0.030149
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
Molly grinned, unfolding the crumpled map. "Okay, the Johnson kid turns six Saturday, backyard party, clown, bouncy castle, mountain of presents." Bill peered over her shoulder nervously. "We are seriously stealing from a toddler? That's low, even for us." "Think big, Bill. Legos, bikes, robot dinosaurs. Kids get the best loot untouched by taxes." He groaned. "Yeah, guarded by twelve sugary ninjas, one tired mom, and a clown who does balloon animals." She whispered. "Please. We dress as clowns, walk in with an empty gift bag, walk out stuffed. Nobody questions extra clowns." "I hate clown makeup. Last time I broke out, and kids cried. I still hear the screaming." "Suck it up, buttercup. You distract with magic tricks while I grab presents and cake." "I don't know magic. I can barely shuffle cards without dropping spaghetti from my sleeves." Molly winked. "Perfect! Kids love spaghetti sleeves. Just yell abracadabra, trip over the bouncy castle, total chaos." Bill gulped. "And if the birthday mom catches us? Do we run, cry, or demand juice boxes like hostages?" "We smile, yell surprise inspection, grab three cupcakes for the road, sprint like caffeinated pirates." "Fine, but I get first pick of Legos." "Deal."
created_at
"2026-09-03T08:22:03.964Z"
9/3/2026, 8:22:03 AM
model
"meta/muse-spark-1.3-20260902"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
90086
moderation_latency
(null)
generation_time
91727
tokens_prompt
75
tokens_completion
307
native_tokens_prompt
68
native_tokens_completion
7074
native_tokens_completion_images
0
native_tokens_reasoning
6769
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
0.0301495
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788423723-blSxyXsjGQPuSsmcKeRq"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788423723-hl6VpzWIpLYHn6j0Ryxd"
upstream_id
"resp_6a992e2c5a50a5d4e3384e90"
provider_responses
0
endpoint_id
"cf4f1b4e-1719-4b65-9111-7dd7635e5a2f"
id
"resp_6a992e2c5a50a5d4e3384e90"
is_byok
false
latency
969
model_permaslug
"meta/muse-spark-1.3-20260902"
provider_name
"Meta"
status
200
total_cost
0.0301495
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%