Run: 2026-11-11-01M753ANGMFPJ92Q2FF0HSZ4G4

Run Details

Duration:
6.1s
Cost:
$0.001666
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 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 crouched behind a hedge wearing a clown wig while Bill balanced a ladder against the fence, both pretending they belonged at a birthday party for a seven year old expecting a pony. Their master plan depended on juice boxes, party hats, and shameless confidence. Molly said, "We sneak in through the bounce house." Bill replied, "That is genius disguised as a felony." Molly whispered, "Grab balloons for camouflage." Bill added, "And cake." Inside, children screamed with joy while a magician attempted card tricks and failed spectacularly with every single card. A mountain of presents sat beside the cake, wrapped in glittering paper that reflected the disco ball above. Molly rehearsed her distraction involving a runaway ferret, although they owned no ferret and had never met one. Bill planned to swap the birthday child's whistle for a kazoo, hoping nobody would notice until the getaway. They argued briefly about whether stealing presents counted as villainy or merely aggressive party crashing with excellent timing. Finally they agreed that cake first, presents second, and running third would guarantee either success or a memorable sugar rush. Then Molly checked her watch, nodded and prepared to ruin the party with theatrical professionalism and snacks.
created_at"2026-11-11T10:44:15.688Z" 11/11/2026, 10:44:15 AM
model"meta/muse-ember-20261109"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2837
moderation_latency(null)
generation_time5842
tokens_prompt75
tokens_completion411
native_tokens_prompt69
native_tokens_completion3318
native_tokens_completion_images0
native_tokens_reasoning2985
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"
usage0.0016659
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.22.2; linux; x64))"
http_referer(null)
request_id"req-1794393855-fZnu8z5fdNdlyeQ77Oa2"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1794393855-ys8KtJd8IrIiuRc51mSL"
upstream_id"resp_6af44701b947e6eef89744a2"
provider_responses
0
endpoint_id"ea8469c2-ddf8-4985-8cf2-f5dc7e63e14c"
id"resp_6af44701b947e6eef89744a2"
is_byokfalse
latency2508
model_permaslug"meta/muse-ember-20261109"
provider_name"Meta"
status200
total_cost0.0016659
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: 10.00%, Deviation: 0.00%
neededCleanfalse
wordsTotal200
wordsDialogue20
100.0000%