Run: 2026-07-25-01KYCVZDKJB9TW8EDF1626T1EA

Run Details

Duration:
1m 54s
Cost:
$0.067844
Provider:
BaseTen

Evaluation summary

Score Evaluator
Details Link
43.38% Matches word count (details)
99.78% Dialogue to Total Word Ratio (details)
71.5800% Overall

Model input

User/Human
You are a author of comedic heist books. Please write a 200 word scene that has 10% 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 spread crumpled blueprints across the hood of a stolen sedan reeking of expired yogurt and questionable decisions, tracing a crayon unicorn that allegedly marked the precise target. The venue was a quiet suburban fortress with inflatable castles, colorful streamers screaming "budget party," and a donkey piñata stuffed with cheap plastic regrets. Bill adjusted his pantyhose mask—three layers for "tactical opacity"—with crooked eyeholes rendering him a disappointed eggplant in the breeze. He studied her annotations with IKEA-lost intensity. "Forty-seven gifts," Molly said, tapping her list. Bill exhaled like a dying accordion. "Barely a misdemeanor." She ignored his legal pessimism, outlining defenses: a vigilant six-year-old consultant with a whistle and Mr. Waffles, a beagle who genuinely hated strangers and shoes. Molly loaded her duffel with candy-cane lockpicks and glitter bombs for "distraction aesthetics," plus clean clothes since felony in denim was uncivilized. Bill contributed beef jerky for canine bribery and an oversized laundry sack for extraction logistics. They synced cheap digital watches to wrong zones for international mystique. "We enter during cake," she decided. Molly zipped her leather jacket with theatrical flair. Bill immediately tripped over the curb, righted himself with dignity, and gestured for her to enter darkness. "Kids are unpredictable," she warned softly. "Bring beef for Mr Waffles," he added practically. "After you, mastermind."
created_at"2026-07-25T14:48:25.989Z" 7/25/2026, 2:48:25 PM
model"thinkingmachines/inkling-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency136
moderation_latency(null)
generation_time112372
tokens_prompt75
tokens_completion14409
native_tokens_prompt75
native_tokens_completion16733
native_tokens_completion_images(null)
native_tokens_reasoning16411
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)
usage0.06784365
router(null)
provider_responses
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endpoint_id"ba2df08c-c0a0-4e0e-9f31-d79a9c475b70"
id"chatcmpl-d9844203ac5f4297af9ba9f70b65493e"
is_byokfalse
latency136
model_permaslug"thinkingmachines/inkling-20260715"
provider_name"BaseTen"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784990906-WspvPMLCCesga9iBN5ir"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784990906-pt0Q9dsWurYUQRIHJSGD"
upstream_id"chatcmpl-d9844203ac5f4297af9ba9f70b65493e"
total_cost0.06784365
cache_discount(null)
upstream_inference_cost0
provider_name"BaseTen"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
43.38% Matches word count n/a
neededCleanfalse
words217
99.78% Dialogue to Total Word Ratio
Ratio: 12.16%, Deviation: 2.16%
neededCleanfalse
wordsTotal222
wordsDialogue27
71.5800%