Run: 2026-09-03-01M1KC11SRYNQ8DCDC02593TMV

Run Details

Duration:
3m 4s
Cost:
$0.068075
Provider:
Phala

Evaluation summary

Score Evaluator
Details Link
100.00% Matches word count (details)
91.01% Dialogue to Total Word Ratio (details)
95.5048% 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

AI
Molly peered through binoculars at a bouncy castle shaped like a purple dinosaur. Beside her, Bill was attempting to fold a floor plan into a paper hat. The van smelled of stale cheese puffs and bad decisions. Through the community center window, a herd of six-year-olds in party hats chased a terrified teenager dressed as a hedgehog. The presents sat on a table shaped like a race car, wrapped in shiny paper that practically begged for a crowbar. Molly counted thirty-seven boxes, including one the size of a small dishwasher. “We are not going through the ball pit again,” she said. “I still have primary-colored plastic in places that don’t get sunlight.” Bill adjusted his paper hat. “Nobody checks the ball pit for duffel bags.” “They check it when you scream because a toddler bites.” Molly tossed the binoculars onto a pile of unpaid parking tickets. She had spent three weeks casing the birthday party of Kevin Trundle, a six-year-old with a trust fund and a mother who hired live ponies for garden parties. The hedgehog theme, according to the invitation Bill had steam-opened, was “a nod to Kevin’s favorite nocturnal animal.” Bill suspected it was because the hedgehog entertainer cost half as much as a pony. The real attraction was the gift table: a glossy mountain of boxes guarded only by a bored magician and a snack table groaning under juice boxes and gluten-free cupcakes. Molly laid out the plan in the tone of a woman who had robbed a christening, two bar mitzvahs, and a funeral reception. She had a gift for turning bouncy castles into crime scenes and no shame. “Here’s the play,” Molly said. “I go in as the pony handler. You’re the pony.” Bill stopped folding. “I’m not being a pony. Last time I was a pony, I threw my back out giving rides to twins.” “This is a hedgehog-themed party. No rides. You just scuttle and occasionally pop a balloon.” “Why can’t I be the hedgehog handler?” “Because you have a getaway-driver voice. While the clown makes balloon swords, knock over the juice bar.” “I’m not knocking over the juice bar. Those little boxes are expensive.” “It’s a diversion. We’re stealing thirty-seven presents, including a possible robot dinosaur or a small safe.” Bill put the paper hat on. He stared at the hedgehog suit in the back of the van, a bristling onesie that had once caused a minor riot at a petting zoo. It smelled of damp socks and regret. He reached for the headpiece. Inside, the terrified hedgehog teenager was cornered by a child wielding a juice box like a shiv. Bill sighed. He could already feel static building in the synthetic spines. Molly handed him gardening gloves and a whistle. “Try to look cute,” she said. “We need the guests distracted, not traumatized.” Bill pulled the headpiece over his face. The eyeholes were misaligned. He adjusted his tail. The things he did for fifty percent of a possible robot dinosaur.
created_at"2026-09-03T10:11:28.71Z" 9/3/2026, 10:11:28 AM
model"deepseek/deepseek-v4-pro-20260813"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1058
moderation_latency(null)
generation_time184259
tokens_prompt75
tokens_completion15316
native_tokens_prompt146
native_tokens_completion15565
native_tokens_completion_images(null)
native_tokens_reasoning14910
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"stop"
service_tier(null)
usage0.0680751
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
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request_id"req-1788430288-bbCITaGFVpH5WfrKSWEE"
session_id(null)
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api_type"completions"
id"gen-1788430288-zci1e0T4nWxZpgsweAEf"
upstream_id"req_9f940242fdfcbffefcdc14af5e0e0a46"
provider_responses
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endpoint_id"bb1fb528-2000-460c-a65e-b82dc347c019"
id"req_9f940242fdfcbffefcdc14af5e0e0a46"
is_byokfalse
latency387
model_permaslug"deepseek/deepseek-v4-pro-20260813"
provider_name"Phala"
status200
total_cost0.0680751
cache_discount(null)
upstream_inference_cost0
provider_name"Phala"
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
words499
91.01% Dialogue to Total Word Ratio
Ratio: 31.37%, Deviation: 1.37%
neededCleanfalse
wordsTotal510
wordsDialogue160
95.5048%