Run: 2026-09-03-01M1M1D836Q2CNZ48E431AA875

Run Details

Duration:
2m 57s
Cost:
$0.026428
Provider:
Phala

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 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 crouched beside the rental van while Bill adjusted his party hat to look less like a man and more like a disappointed uncle. "Bill, if we steal every present, the party becomes a crime scene made of glitter, balloons, and small, accusing eyebrows." Across the lawn, the Hendersons were holding a party for eight children, six grandparents, and one extremely confident puppy. Streamers twisted in the breeze like thin red flags of surrender. A banner read Happy Birthday Leo in letters that had survived exactly three hours of wind. The presents lay in the gazebo, wrapped in shiny paper, tied with ribbons, and arranged with the confidence of furniture that expected to be judged. "We take the toys, Bill, not the cupcakes, though I suspect the cupcakes are the real treasure, and I am not above a bite." Molly opened the trunk and revealed a kit of tools that belonged in a mystery novel written by a man who trusted nothing, especially birthday parties. She lifted a lockpick, a silk scarf, a tiny mirror, and a bag of plastic coins that looked suspiciously like real change except for the fact that every coin said LOL on one side. "The parents are in the garden judging each other's hats, the kids are in the hall chasing a plastic dinosaur, and the presents are stacked behind a curtain like a very colorful vault." Bill checked his watch, then checked the hedge, then checked the hedge again, as if repetition could make the operation look less ridiculous. He smoothed his cardigan, pulled a birthday noose from his pocket, and folded it with the tenderness of a surgeon preparing for a small, sweet tragedy. "We enter as cleanup volunteers, you carry the big box, I carry the tiny box, and our signal is three polite coughs from near the gift table." The gazebo door had one lock and a brass knob shaped like a smiling starfish. Molly nodded at it with the respect one gives to a minor obstacle. Bill nodded back, because in heist work, nodding is often the loudest sound a thief makes before getting caught. "If a child asks questions, you become the tooth fairy, and if a parent asks questions, we become the tooth fairy with a van." They slipped through the hedge, over the toy box, and into the gazebo. Each wrapped package stood like a small monument to childhood greed. Bill placed the big box on the floor, and the tiny box chose itself a spot beside a wrapped present with a rocket ship on it. "Good plan, Bill, because I have already hidden the glitter bag, the ribbon scissors, and the emergency donut under the passenger seat." Molly coughed once, twice, three times. Bill understood. He lifted the big box while Molly lifted the tiny box, and together they moved toward the van with the solemn joy of thieves who had not yet considered whether the presents were heavier than fame before the party could end.
created_at"2026-09-03T16:25:08.462Z" 9/3/2026, 4:25:08 PM
model"qwen/qwen3.8-27b-20260814"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency366
moderation_latency(null)
generation_time176507
tokens_prompt75
tokens_completion7029
native_tokens_prompt186
native_tokens_completion8792
native_tokens_completion_images(null)
native_tokens_reasoning8193
native_tokens_cached64
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"stop"
service_tier(null)
usage0.026428
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788452708-LwtUt2XbRIWcszkiEavY"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788452708-O42uCc1gjTUbL4aI3yN0"
upstream_id"req_41ec4c3abd24fbac09c33a8795f32492"
provider_responses
0
endpoint_id"cfc4d0ca-df7c-4b5f-9c74-328c41a7cbc3"
id"req_41ec4c3abd24fbac09c33a8795f32492"
is_byokfalse
latency366
model_permaslug"qwen/qwen3.8-27b-20260814"
provider_name"Phala"
status200
total_cost0.026428
cache_discount0.0000224
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
words500
100.00% Dialogue to Total Word Ratio
Ratio: 30.00%, Deviation: 0.00%
neededCleanfalse
wordsTotal500
wordsDialogue150
100.0000%