Run: 2026-11-11-01M7545WHZMZF7SVWQT2Q7PVZM

Run Details

Duration:
5.9s
Cost:
$0.001898
Provider:
Meta

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 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
Molly spread blueprints across the kitchen table as Bill sharpened a candy cane. "Okay, Bill, the plan is simple: we enter the birthday party, distract the clown, and hoover up every present like very polite vacuum cleaners." "But the party is for kids. What if they ask us to play pin the tail on the donkey?" "Then we play. We win the prize, because losing to a child looks suspicious, and suspicious people get no cake." "What about the bouncy castle guard? He has a whistle, a clipboard, and the unshakeable confidence of a man named Chad." "We bribe Chad with juice boxes. Every adult folds instantly when offered apple juice and a paper umbrella." "And the parents? They will definitely notice two adults absconding with a mountain of wrapped bicycles and shouting, mine!" "That is why we wear disguises. I bought us matching tiger costumes, which are both adorable and legally distracting." Bill adjusted his tiny tiger hat proudly. "Tigers cannot open doors. Their paws are terrible. We tested this morning, and now the doorknob is glittery." "Excellent. Glitter means we were never here. Now, Bill, hand me the trolley, and try not to cry again." "Too late, Molly!"
created_at"2026-11-11T10:59:07.467Z" 11/11/2026, 10:59:07 AM
model"meta/muse-ember-20261109"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1475
moderation_latency(null)
generation_time5827
tokens_prompt75
tokens_completion310
native_tokens_prompt69
native_tokens_completion3782
native_tokens_completion_images0
native_tokens_reasoning3492
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"completed"
service_tier"default"
usage0.0018979
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer(null)
request_id"req-1794394747-gQHPMNOgYS8VC3JkLfA7"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1794394747-YzlO5ny4poE0cUkf432F"
upstream_id"resp_6af44a7caee41965555b43bc"
provider_responses
0
endpoint_id"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id"resp_6af44a7caee41965555b43bc"
is_byokfalse
latency722
model_permaslug"meta/muse-ember-20261109"
provider_name"Meta"
status200
total_cost0.0018979
cache_discount(null)
upstream_inference_cost0
provider_name"Meta"
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
words200
100.00% Dialogue to Total Word Ratio
Ratio: 90.00%, Deviation: 0.00%
neededCleanfalse
wordsTotal200
wordsDialogue180
100.0000%