Run: 2026-09-03-01M1K9KYSYTCHMYXKVK0F7W3TR

Run Details

Duration:
9m 31s
Cost:
$0.014470
Provider:
Mancer 2

Evaluation summary

Score Evaluator
Details Link
68.10% Matches word count (details)
93.28% Dialogue to Total Word Ratio (details)
80.6892% 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
The van was a monument to failure, parked in the shadows of a pristine cul-de-sac, its paint peeling like sunburned skin. Molly, a woman who could crack a safe with a stern look and a bobby pin, was hunched over a laminated floor plan of the Whitfield residence. Her finger, stained with engine grease, traced a dotted line from the back gate, through a narrow hedge, and straight into the living room where the gift table would be groaning under the weight of expensive plastic. Bill, her accomplice, was not looking at the plan. He was trying to dislodge a gummy bear from his molar with his tongue, a task that seemed to demand more concentration than any heist they had ever attempted. The clock on the dashboard ticked with the patience of a bored god. Outside, the sound of a lawnmower buzzed like a distant swarm of angry bees. The van's upholstery was torn, and a spring poked through the driver's seat like a stubborn weed. Bill had once used it to fish a stolen watch out of a vent. Molly ignored him, her focus absolute. The map was covered in coffee rings, each one a silent testament to a previous near-miss. He sighed, the sound escaping like a deflating balloon. A fly buzzed against the windshield. The air in the van was thick with the smell of stale coffee and the faint, acrid tang of a plan that was already going sideways in his mind. He finally gave up on the candy, swallowing it whole with a grimace. Molly's eyes were fixed on the blueprint, tracing the angles of the windows. She didn't look up when she spoke. Her voice was flat, clinical, as if she were reading a grocery list. "Okay," Bill said. "Why are we doing this? Stealing from kids?" "Because the Whitfields are rich. Their kid gets a mountain of presents." Molly tapped the map with a decisive finger. "Magician at 3:00. Gives us 17 minutes. Seventeen minutes." "Still seems wrong." Bill rubbed the back of his neck, feeling the sweat gather there. "It's redistribution." She traced a line. "Trust me." "What if the kids see us?" Bill squinted. "We have a goat. Painted a sign. Says 'Pony.'" Molly smiled thinly. "A goat?" Bill blinked. "It's a decoy. If that fails, we taser the late clown." She pulled out the taser. "You're going to taser a clown?" Bill's voice rose. "Only if he gets in the way." Molly's voice was calm. "The mother is the problem. She'll hover over the gift table." "So?" "We let the goat eat the cake. She runs to the kitchen. We grab the gifts." Molly leaned back. "And the kids in the room?" Bill asked. "I'll ask for directions to the bathroom. They love helping." Molly's smile was cold. "You're terrifying." Bill shook his head. "That's the job. Start the van." Molly folded the map. "We've got a party to crash." "Really?" Bill said. "Really." Molly said. "And the goat?" Bill asked. "The goat is the key." Molly said. "Alright," Bill said. "Let's go."
created_at"2026-09-03T09:29:22.676Z" 9/3/2026, 9:29:22 AM
model"deepseek/deepseek-v4-flash-20260731"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1044
moderation_latency(null)
generation_time569642
tokens_prompt75
tokens_completion23913
native_tokens_prompt67
native_tokens_completion28918
native_tokens_completion_images(null)
native_tokens_reasoning23179
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)
usage0.01447
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
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request_id"req-1788427762-Bk1VmQx9sh0iGDt6JzMz"
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api_type"completions"
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upstream_id"01a0669a02890083"
provider_responses
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endpoint_id"14c4df90-c7af-42ff-99e7-69d62a89e7d5"
is_byokfalse
latency1099
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"AkashML"
status429
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endpoint_id"223c54e7-4db1-4098-980f-47741e7637ab"
is_byokfalse
latency389
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"Baidu"
status429
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endpoint_id"9c83b6fb-0614-4d50-b30b-123a09ba354a"
id"01a0669a02890083"
is_byokfalse
latency1018
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"Mancer 2"
status200
total_cost0.01447
cache_discount(null)
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provider_name"Mancer 2"
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data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
68.10% Matches word count n/a
neededCleanfalse
words514
93.28% Dialogue to Total Word Ratio
Ratio: 28.82%, Deviation: 1.18%
neededCleanfalse
wordsTotal517
wordsDialogue149
80.6892%