Run: 2026-09-10-01M25DVY38Z45VYE8PPZQ5SDQE

Run Details

Duration:
15.1s
Cost:
$0.004175
Provider:
Novita

Evaluation summary

Score Evaluator
Details Link
100.00% Matches word count (details)
36.79% Dialogue to Total Word Ratio (details)
68.3935% Overall

Model input

User/Human
You are a author of comedic heist books. Please write a 200 word scene that has 90% 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
"Okay, Bill, the target is a seven-year-old's unicorn birthday party." "Molly, I've robbed casinos. Why are we stealing from tiny people?" "Because casinos have cameras. Tiny people have cake." "And gift tables." "Exactly. You distract the clown. I'll handle the presents." "The clown? Last time you said that, I ended up juggling flaming torches." "That was a fundraiser. This is a party." "What's the cover?" "We're the magician's assistants." "We don't have a magician." "Bill, we have a disappearing act. Us. With the presents." "The mom will notice." "She'll be busy with pin the tail on the donkey." "That game is dangerous. I got pinned once." "You got pinned at a wedding." "Same energy. What about the kids?" "Give them cake. Sugar is a smoke bomb." "And if a kid sees us?" "Tell them we're elves auditing the gift inventory." "Elves aren't real." "Neither are our alibis. Move." "What about the dog?" "What dog?" "The birthday dog. It's wearing a party hat." "Then we bring sausages." "To a kids' party? That's unethical." "Bill, we're stealing a scooter and fourteen stuffed llamas." "Fine. But I'm not missing cake." "Deal. Presents first, frosting second." "Frosting first." "Deal." "And no biting." "Agreed."
created_at"2026-09-10T10:29:57.998Z" 9/10/2026, 10:29:57 AM
model"deepseek/deepseek-v4.1-flash-20260910"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency992
moderation_latency(null)
generation_time15068
tokens_prompt75
tokens_completion3089
native_tokens_prompt93
native_tokens_completion3456
native_tokens_completion_images(null)
native_tokens_reasoning3148
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)
usage0.0041751
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1789036198-lF5sGtdDx0UH6kd892Jf"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1789036198-mqum9qE9twJ0XpWnksxs"
upstream_id"5b3a4925998af2d8c59bf5bb9c23434e"
provider_responses
0
endpoint_id"dac120e6-b2d2-44d4-8698-07844c6b84da"
id"5b3a4925998af2d8c59bf5bb9c23434e"
is_byokfalse
latency406
model_permaslug"deepseek/deepseek-v4.1-flash-20260910"
provider_name"Novita"
status200
total_cost0.0041751
cache_discount(null)
upstream_inference_cost0
provider_name"Novita"
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
words199
36.79% Dialogue to Total Word Ratio
Ratio: 100.00%, Deviation: 10.00%
neededCleanfalse
wordsTotal201
wordsDialogue201
68.3935%