NC Bench
Overview
About
Tests
Models
Model
Qwen 2.5 72B
Test
Dialogue tags
Scenario
Write 500 words with 30% dialogue
Run ID
2024-09-20-01J881N5EA77N705NKYP9HR6XS
Model input
User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 30% 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 leaned back in her creaky armchair, eyeing the stack of colorful invitations on the coffee table. Bill, her longtime partner in crime, was sprawled on the couch, fiddling with a set of lock-picks. “Those presents are just begging for a good heist,” Molly said, her eyes twinkling with mischief. Bill looked up, a grin spreading across his face. “You know, this could be our finest hour. A whole bunch of loot just sitting there, wrapped up and ready for the taking.” “Exactly,” Molly replied, her fingers tracing the glittery edges of one of the invites. “We’ve got to plan this right. We can’t just waltz in and grab the goods. We need to blend in.” Bill chuckled, “I don’t think ‘waltzing in’ is our style, Mol. But you’re right. We need a cover. How about we go as clowns?” Molly raised an eyebrow. “Clowns? Are you serious? We’d stick out like sore thumbs.” Bill pouted. “Hey, it was worth a shot. What do you suggest then?” “Let’s be the entertainment. Face-painting, balloon animals, that sort of thing. We can stay close to the loot and make our move when the time is right.” Bill nodded, a slow smile spreading across his face. “Genius. And we can use the distraction to our advantage. I can make some balloon animals that look suspiciously like weapons if we need a quick getaway.” Molly laughed. “Balloon animals as weapons? That’s a new one. But I like it. We’ll need to practice though. I’m not exactly a pro at face-painting.” “No worries, I’ll teach you. It’s all in the wrist,” Bill said, demonstrating with an invisible brush. Molly rolled her eyes. “Sure, sure. What about the logistics? When do we make our move?” Bill consulted the invitation. “The party starts at 2 PM. We should arrive early, scope out the place, and get into our roles.” Molly nodded. “Good. We can set up our area near the gift table. That way, we’ll have a clear view of everything.” “Right. And we’ll need to keep an eye on the parents. They might get suspicious if we’re too obvious,” Bill added. Molly sighed. “Parents are always a wildcard. But if we play our cards right, they’ll be too busy with the cake and the cake-faced kids to notice us.” Bill laughed. “Cake-faced kids. I like that. We could even offer to help with the cake. That would give us an excuse to be near the gift table.” “Perfect. And we can use the cake as a distraction if things get hairy. Cake is a great diversion tactic.” “Agreed. Speaking of cake, we should probably get some supplies. Face paints, balloons, and maybe a couple of costumes,” Bill said, getting to his feet. Molly stood up as well. “Let’s hit the party store. And while we’re there, we can pick up some tools for the job.” Bill nodded, slipping his lock-picks into his pocket. “Sounds like a plan. This is going to be our most delightful heist yet.” Molly grinned, her eyes gleaming with excitement. “You bet it is. Let’s go round up some loot, Bill. It’s time to make some children very happy—and some parents very confused.”
id
"gen-sPLOExJNcxD463yD0jGlIhN6jnI6"
total_cost
0.000324
upstream_id
"chat-40929ac98feb4b21bdcb04fe0628ec35"
created_at
"2024-09-20T15:44:08.653778+00:00"
Friday, September 20th, 2024 at 3:44:08 PM GMT+00:00
model
"qwen/qwen-2.5-72b-instruct"
app_id
182717
streamed
true
cancelled
false
provider_name
"Hyperbolic"
latency
281
moderation_latency
(null)
generation_time
16941
finish_reason
"stop"
tokens_prompt
78
tokens_completion
725
native_tokens_prompt
83
native_tokens_completion
727
native_tokens_reasoning
(null)
num_media_prompt
(null)
num_media_completion
(null)
origin
"https://ncbench.com/"
usage
0.000324
Evaluation details
Result
Evaluator
Details
Meta Data
0.0000%
Matches word count
n/a
neededClean
false
words
537
0.0000%
Dialogue to Total Word Ratio
Ratio: 75.23%, Deviation: 45.23%
neededClean
false
wordsTotal
537
wordsDialogue
404
0.0000%