Run: 2026-09-10-01M25DXH9VXMS5H7ES95M8BTV1

Run Details

Duration:
1m 27s
Cost:
$0.014430
Provider:
DeepSeek

Evaluation summary

Score Evaluator
Details Link
99.98% Matches word count (details)
97.39% Dialogue to Total Word Ratio (details)
98.6883% Overall

Model input

User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 70% 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
Bill and Molly sat in his mother’s minivan outside a pink house. A bouncy castle wheezed on the lawn. Inside, thirty children screamed at a magician while parents filmed. A clown balloon sagged from the mailbox. Bill drummed the dashboard. “Remind me why we’re robbing a six-year-old’s party instead of a bank?” Molly checked her lipstick in the rearview mirror. “Banks have guards. Parties have cake and distracted parents.” “We’re risking prison for party bags.” “Not just party bags. Presents. Unopened. Unregistered.” “Right. We hit the pile during the magic show.” Molly unfolded a party flyer. The cover showed a smiling dinosaur. “New plan. We arrive as entertainment.” “Clowns?” “Balloon artists.” “I hate balloons. They pop like our alibi.” “Then we’re distant cousins. Uncle Bill and Aunt Molly. We bring a gift and case the pile.” Bill showed a tattoo of a skeleton holding a crowbar. “Blend in? With this?” “Wear a cardigan.” “Yours?” “It smells like mothballs and poor decisions. Perfect.” Molly zipped open a duffel bag labeled LIBRARY BOOKS. Bill wiped sweat from his forehead. A parent nearby took photos of the bouncy castle. Molly drew a diagram on a napkin. She circled the dining table in red ink. “Party starts at two. Presents go on the dining table. At two-fifteen, the magician starts. At two-twenty, we strike.” “At two-twenty, I’ll be comforting a kid who wet his pants during Pin the Tail on the Donkey.” Bill practiced a helpful smile. “Nobody suspects the guy holding a trash bag full of Legos either.” “We use gift bags. Presentation matters.” “Fine. We steal the presents, bag them, and walk out like helpful relatives.” “To your mother’s minivan. She’s picking up a sofa at three.” “Then we’re quick. In, out, no witnesses.” “Thirty witnesses. All under four feet tall and hopped up on frosting.” A pinata shaped like a unicorn swung from a tree. A toddler licked the minivan window. “Kids are unreliable. They’ll say a dinosaur did it.” “One kid saw me steal a cookie and called me a raccoon.” “See? Unreliable.” “And the parents?” “Phones. We’ll be fine.” “What about the birthday kid?” “We leave one present. The cheap one. For morale.” “What’s my job?” “Distract the magician. Pretend to be his assistant.” “He’ll know.” “Not if you say abracadabra with confidence.” Molly adjusted an imaginary bow tie. “I don’t have confidence. I have a hernia and a record.” Bill flexed his fingers. “Same energy. Exit through the kitchen.” “The kitchen has the cake.” “So we take the cake too.” “Bill, we’re not stealing the cake.” “Why not?” “Because that’s a monster move. Presents, yes. Cake, no.” “Fine. But if there’s ice cream, I’m not leaving it.” “Deal. Now let’s go buy a card.” “A card?” “We can’t show up empty-handed.” “We’re literally there to empty-hand them.” “Exactly. So we bring one tiny gift. Investment.” “I hate that you’re right.” “I hate that I’m right too. Let’s rob a toddler.” Bill started the minivan. The engine coughed like a smoker.
created_at"2026-09-10T10:30:50.432Z" 9/10/2026, 10:30:50 AM
model"deepseek/deepseek-v4.1-flash-20260910"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency885
moderation_latency(null)
generation_time86864
tokens_prompt75
tokens_completion21349
native_tokens_prompt93
native_tokens_completion24027
native_tokens_completion_images(null)
native_tokens_reasoning23237
native_tokens_cached0
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)
usage0.01443015
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1789036250-Gteg7uiwjZXyhSPBHoBw"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1789036250-v3yBLrWQ1u1U6BSDaWxj"
upstream_id"913aa93e-be4c-4005-bbd0-29208d03a831"
provider_responses
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endpoint_id"fd104bc8-535a-4d31-a847-a8e402e86a02"
id"913aa93e-be4c-4005-bbd0-29208d03a831"
is_byokfalse
latency335
model_permaslug"deepseek/deepseek-v4.1-flash-20260910"
provider_name"DeepSeek"
status200
total_cost0.01443015
cache_discount(null)
upstream_inference_cost0
provider_name"DeepSeek"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
99.98% Matches word count n/a
neededCleanfalse
words502
97.39% Dialogue to Total Word Ratio
Ratio: 70.73%, Deviation: 0.73%
neededCleanfalse
wordsTotal509
wordsDialogue360
98.6883%