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Run: 2026-03-18-01KM07WDDK1JQDJYDNWB6F4ERJ
Run Details
Model:
GPT-5.4 Nano (Reasoning)
Test:
Dialogue tags
Scenario:
Write 500 words with 30% dialogue
Duration:
9.9s
Cost:
$0.001663
Provider:
OpenAI
Evaluation summary
Score
Evaluator
Details Link
0.00%
Matches word count
(details)
0.00%
Dialogue to Total Word Ratio
(details)
0.0000%
Overall
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 crouched behind a stack of delivery boxes as if cardboard could offer witness protection. Through the gap in the curtains, the neighborhood’s community center glowed with party lights—tiny stars pasted to the windows, a banner that said HAPPY BIRTHDAY, and the unmistakable sound of children laughing like wind chimes with glue on them. Bill checked the strap of his disguise for the third time. It was a pirate hat, a few sizes too big, and a shirt that still smelled faintly of laundry detergent and regret. “This is it,” Molly whispered, patting the pocket of her bag. “The Great Present Take. Phase One: look casual.” Bill leaned closer. “I’m born casual.” “You are born suspicious,” Molly said. “Casual people don’t say ‘born.’” Bill gave her a grin that could melt frosting. “Fine. Phase One: look like we belong.” Molly nodded toward the entrance where a balloon arch bobbed like it was trying to escape. “We’re going in dressed as… birthday helpers.” Bill raised a finger. “But are we helpers, or are we… celebratory opportunists?” Molly sighed. “Helpers. Opportunists are what the police call you when they’re bored.” Bill’s eyes flicked to the timer on the wall inside. “I brought a cake-flavored decoy.” “You brought a cake-flavored decoy?” Molly repeated. “It’s for misdirection,” Bill said proudly. “If someone notices us, we can offer the decoy cake and run away.” “That’s not misdirection,” Molly said. “That’s sugar bribery.” “It’s both,” Bill argued. A muffled cheer rose from inside. The sort of cheer that made grown-ups smile without knowing why. Molly tilted her head, listening. “I can hear the magician.” Bill groaned. “Of course there’s a magician. Last time we did a job there was a DJ who played thirty-seven minutes of ‘Baby Shark.’” “This time,” Molly said, “we’re stealing all the presents. Every last one.” Bill’s shoulders squared. “All the presents. Even the ones that look like they’re definitely from Aunt Linda.” Molly gave him a hard look. “Especially those. Aunt Linda brings the best bow.” Bill nodded solemnly, as if he were swearing an oath to ribbon. “Okay, boss. Plan.” Molly pulled a notepad from her coat and immediately frowned at the scribbles. “Your handwriting is terrible.” “It’s pirate handwriting,” Bill said. “It’s just… chaotic.” Molly cleared her throat and wrote her own notes on top of his. “We enter quietly. We blend. We don’t touch anything that jingles like it’s going to report us.” Bill pointed at his pocket. “My pocket jingles.” “It’s coins,” Molly said. “They’re not even ours.” Bill shrugged. “I like options.” Molly lowered her voice. “Remember: no heroics. We’re not stealing from children. We’re stealing for a higher purpose.” Bill blinked. “Higher purpose?” Molly met his eyes. “We’re redistributing joy.” Bill opened his mouth, then paused. “That sounds illegal.” “It’s metaphorical,” Molly said quickly. “Like… taxes, but funnier.” Bill seemed to consider this. “Do you think children know when you steal presents?” Molly leaned in. “Children know when you disappoint them. Adults know when you steal. We’ll avoid both.” Bill adjusted the pirate hat so it covered one eye comically. “I can do avoid. I’m extremely good at avoid.” A door clicked inside—someone repositioning the chairs for games. Molly and Bill held perfectly still, like two statues that had forgotten what they were made of. Bill whispered, “If we get caught, what do we say?” Molly didn’t hesitate. “We say we’re here for the… party supplies.” Bill nodded. “Party supplies. Like tape and—” “And cake,” Molly finished. Bill brightened. “I can carry cake.” Molly looked at his hands. “You can carry cake. You cannot carry cake quietly.” Bill’s smile faltered. “I can try.” Molly pulled him closer, their disguises brushing like mismatched book covers. “Bill. Tonight, we are ghosts of generosity. We swoop in, collect the boxes, and leave before anyone realizes the birthday magic has… temporarily relocated.” Bill whispered back, reverent, “Birthday magic relocated. That’s poetic.” “It’s not poetic,” Molly said. “It’s efficient.” From inside, a child shouted, “Where’s the loot bag?” and another voice—probably an adult—answered, “In a second, sweetheart!” Molly exhaled. “Second starts now.” Bill flexed his fingers. “Okay. Tell me we’re doing this.” Molly’s grin returned, sharp and delighted. “We’re doing this.” Bill’s eyes gleamed. “All presents.” “All presents,” Molly confirmed, and together they slid toward the door like misbehaving shadows—ready to steal every last bright box before the birthday party could finish being happy.
created_at
"2026-03-18T10:29:24.544Z"
3/18/2026, 10:29:24 AM
model
"openai/gpt-5.4-nano-20260317"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
7891
moderation_latency
(null)
generation_time
9562
tokens_prompt
77
tokens_completion
1611
native_tokens_prompt
66
native_tokens_completion
1320
native_tokens_completion_images
0
native_tokens_reasoning
247
native_tokens_cached
0
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"completed"
usage
0.0016632
router
(null)
provider_responses
0
endpoint_id
"0c835f2e-c18d-4e8c-b245-e1e3bd08b97f"
id
"resp_0b04255f0a5439780169ba7e849b288193b48f854ebe3bc2b2"
is_byok
false
latency
193
model_permaslug
"openai/gpt-5.4-nano-20260317"
provider_name
"OpenAI"
status
200
user_agent
"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer
(null)
api_type
"completions"
id
"gen-1773829764-SHLCJQTlCMRUQ2JVdLvA"
upstream_id
"resp_0b04255f0a5439780169ba7e849b288193b48f854ebe3bc2b2"
total_cost
0.0016632
cache_discount
(null)
upstream_inference_cost
0
provider_name
"OpenAI"
Evaluation details
Result
Evaluator
Details
Meta Data
0.00%
Matches word count
n/a
neededClean
false
words
739
0.00%
Dialogue to Total Word Ratio
Ratio: 47.38%, Deviation: 17.38%
neededClean
false
wordsTotal
743
wordsDialogue
352
0.0000%