Run: 2026-07-25-01KYD59GS540MTGQ8PHCVVC5KR

Run Details

Duration:
22.1s
Cost:
$0.016801
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

AI
Molly stared at the glittery invitation taped to their dented van dashboard while Bill wrestled with an overinflated balloon animal. "We can't just walk in wearing that, Bill. That's not clown makeup, that's ketchup." Bill grinned, scraping dried condiment from his cheek with dramatic pride. "Kids love ketchup. Look, it's interactive art." The backyard ahead overflowed with screaming toddlers, deflated bounce house, and a mountain of brightly wrapped presents guarded by vigilant mothers. "Okay, how do we grab them without getting tackled by moms?" "We cause distraction. You cry like a child, I loot." She snorted. "I am not crying on command. Find another genius plan." Bill produced a squeaky unicorn pinata and a comically enormous laundry sack. "Fine, we steal pinata, kids chase candy, we take presents. Simple." Molly eyed the sugar-fueled chaos, then the pile beside the juice boxes, thinking hard. "That's actually less dumb than usual. Let's do it before sugar crash." They pulled striped hats low, checked their sack for holes, and marched toward destiny smelling faintly of ketchup. "Remember, no pushing toddlers, Bill, and no eating frosting off floor." "Deal, but if I see chocolate, protocol changes." He nodded. "Let's steal some birthday cheer, partner."
created_at"2026-07-25T17:31:14.093Z" 7/25/2026, 5:31:14 PM
model"meta/muse-spark-1.1-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency20765
moderation_latency(null)
generation_time21979
tokens_prompt75
tokens_completion332
native_tokens_prompt225
native_tokens_completion3887
native_tokens_completion_images0
native_tokens_reasoning3592
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"completed"
service_tier"auto"
usage0.016801
router(null)
provider_responses
0
endpoint_id"b2b9f6f9-8880-41c1-bd0c-867650fd5238"
id"resp_6a64f2e237544aa5fc3f4d35"
is_byokfalse
latency257
model_permaslug"meta/muse-spark-1.1-20260709"
provider_name"Meta"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1785000674-90Qygee8kEDDvSwZAaQ2"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1785000674-6KJbZtU2phtippAVbJEO"
upstream_id"resp_6a64f2e237544aa5fc3f4d35"
total_cost0.016801
cache_discount(null)
upstream_inference_cost0
provider_name"Meta"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Matches word count n/a
neededCleanfalse
words200
100.00% Dialogue to Total Word Ratio
Ratio: 49.75%, Deviation: 0.25%
neededCleanfalse
wordsTotal201
wordsDialogue100
100.0000%