Run: 2026-09-03-01M1K5K42CAV14P1KMX3H36M1Z

Run Details

Duration:
28.0s
Cost:
$0.021237
Provider:
Meta

Evaluation summary

Score Evaluator
Details Link
100.00% Matches word count (details)
99.76% Dialogue to Total Word Ratio (details)
99.8806% Overall

Model input

User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 70% 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 spread the blueprint across the greasy pizza box and stabbed a juice-stained backyard with her finger. "Okay Bill the target is little Timmy's seventh birthday party. Laser tag bouncy castle clown and a mountain of presents piled by the cake table." Bill stared at the glittery invitation like it might explode. "Are you serious Molly? Last week you said we were hitting the bank on Fifth Street and now we're robbing a kid?" She grinned and pulled out a list laminated in crayon. "The bank installed motion sensors Timmy's mom installed a Pinterest arch. Also do you know what an untouched Lego Death Star goes for online?" Bill rubbed his forehead already feeling the sugar crash coming. "So what's the master plan? We walk in and just grab boxes while screaming children pelt us with juice boxes?" Molly flipped the pizza box over revealing a surprisingly detailed tactical diagram involving streamers and sprinklers. "We go undercover Bill. You will be Mr. Wiggles the clown with the squeaky shoes and I will be Princess Sparkleface with authority over all children." Bill choked on his coffee. "No way I'm wearing clown shoes again Molly. Last time I tripped over my own feet and landed inside the jewelry case at Henderson's." She ignored him and tapped the diagram where a large X marked the presents. "Focus. The presents are stacked behind the gift table guarded by Timmy's grandma. She's got eyes like a hawk and she knits very aggressively." Bill leaned closer squinting at the tiny stick figures she had drawn. "Okay so how do we get past Grandma Knits-A-Lot without getting stabbed with a needle?" Molly produced two glittery costumes from a trash bag with a flourish. "We distract her. You do balloon animals until she is charmed and I will hook the presents with the extendable grabber hidden in my wand." Bill held up the floppy red nose with deep suspicion. "And if the kids notice two adults stealing their loot and start crying louder than a fire alarm?" Molly smiled the way she always did before a terrible idea became brilliant. "We bring cake Bill. No child has ever resisted double chocolate cake. While they swarm it we load the wagon and vanish like magic." Bill sighed and started squeezing into the polka dotted pants that squeaked with every step. "Fine but if Timmy cries I quit. Also I want first pick of the Legos and no you cannot keep the bouncy castle." Bill tugged the wig straight. Molly laughed. "Deal. But remember act natural smile wide and if anyone asks your clown name is Mr. Wiggles who loves children and definitely does not have a criminal record." "Perfectly natural. I was born to entertain terrifying seven year olds for stolen plastic bricks. Let's go steal some joy." "That's the spirit Bill. After this we can finally afford that getaway van with working brakes." "And maybe earplugs for the screaming?" "Absolutely. Earplugs are non negotiable partner." "Let's roll Princess."
created_at"2026-09-03T08:19:00.818Z" 9/3/2026, 8:19:00 AM
model"meta/muse-spark-1.2-20260805"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3412
moderation_latency(null)
generation_time27970
tokens_prompt75
tokens_completion869
native_tokens_prompt68
native_tokens_completion4977
native_tokens_completion_images0
native_tokens_reasoning4205
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
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origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"completed"
service_tier"auto"
usage0.02123725
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788423540-1A3WXLmkztTiKz4dB2Ga"
session_id(null)
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api_type"completions"
id"gen-1788423540-iDBvxIibNZCbE9BD6YQO"
upstream_id"resp_6a992d7562c1f7bb45f44342"
provider_responses
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endpoint_id"ffc8e76e-808a-44d2-bd21-c6ac16e721cb"
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is_byokfalse
latency1315
model_permaslug"meta/muse-spark-1.2-20260805"
provider_name"Meta"
status200
total_cost0.02123725
cache_discount(null)
upstream_inference_cost0
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
neededCleanfalse
words500
99.76% Dialogue to Total Word Ratio
Ratio: 69.78%, Deviation: 0.22%
neededCleanfalse
wordsTotal503
wordsDialogue351
99.8806%