Run: 2026-09-03-01M1K52JP9F6GYGKMMP52TDR2K

Run Details

Duration:
2m 12s
Cost:
$0.041412
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 500 word scene that has 50% 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
The basement smelled of old socks and stolen cake as Molly spread crayon maps across the wobbly table while Bill chewed cold pizza crusts nervously. "Listen Bill we have to sneak into that birthday party for children and grab every shiny present before the clown starts crying loudly today please." Bill groaned and wiped crumbs from his jacket while a broken ceiling fan clicked above them sending dust onto the stolen party invitation list slowly. "Are you crazy Molly those kids are vicious last time a toddler bit my thumb and I still have teeth marks shaped like tiny dinosaurs." Molly tapped a red marker against the drawing of the house with arrows pointing to windows doors and a suspicious trampoline near the fence line. "Stop whining you big baby we will dress as entertainers I will be the magician you can be the balloon animal disaster with squeaky pants." Bill shuddered at the thought of squeaky latex while Molly tossed him a striped clown wig that smelled faintly of popcorn and regretful choices made. "I hate balloons Molly they pop loudly and smell like rubber and last year a mime trapped me in an invisible box for hours dude." Outside rain pattered on the tiny window as Molly outlined the cake table location with dramatic circles and Bill sketched a getaway tricycle route quickly. "Focus Bill the presents are piled by the cake table Lego sets game consoles candy bags we grab them in the big laundry sack quickly." Bill paced in circles knocking over empty soda cans while picturing angry mothers wielding phones like weapons and grandmothers flexing massive arms nearby very menacingly. "What about parents Molly there will be mothers with cameras fathers with barbecue forks and one grandmother who looks like she wrestles bears professionally man." Molly grinned wickedly and pulled a sack from under the couch releasing dust bunnies while Bill imagined chaos screaming and sugary pandemonium erupting everywhere fast. "We distract them with sugar Bill you release the puppies from the shelter van while I sing happy birthday terribly off key until everyone screams." The ceiling fan wobbled harder as Bill scratched his beard thinking of teary eyes and Molly rolled her eyes so hard they nearly stuck forever. "That might work but what if the birthday boy cries Molly I cannot handle tears last time I returned a wallet because someone frowned sadly." Molly demonstrated the perfect fake smile in the cracked mirror while Bill practiced stuffing pillows under his shirt and waddling like a guilty penguin thief. "Then we give him a balloon Bill we smile we say happy birthday champ while stuffing the good toys down our pants like total professionals." "Fine but if a child glues glitter to my face again I am keeping the biggest present for myself and eating all the frosting straight." They shook hands solemnly as thunder rumbled outside and the crayon map fluttered off the table landing neatly into the laundry sack ready for tomorrow.
created_at"2026-09-03T08:09:58.736Z" 9/3/2026, 8:09:58 AM
model"meta/muse-spark-1.3-20260902"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3849
moderation_latency(null)
generation_time132116
tokens_prompt75
tokens_completion765
native_tokens_prompt68
native_tokens_completion9724
native_tokens_completion_images0
native_tokens_reasoning9111
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"auto"
usage0.041412
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788422998-LcN0wts1juwzLQqMl2R6"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788422998-1pzjGFHcEgpn8gvEdYsk"
upstream_id"resp_6a992b57f9f43ad28e8a44e5"
provider_responses
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endpoint_id"cf4f1b4e-1719-4b65-9111-7dd7635e5a2f"
id"resp_6a992b57f9f43ad28e8a44e5"
is_byokfalse
latency889
model_permaslug"meta/muse-spark-1.3-20260902"
provider_name"Meta"
status200
total_cost0.041412
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
words500
100.00% Dialogue to Total Word Ratio
Ratio: 50.00%, Deviation: 0.00%
neededCleanfalse
wordsTotal500
wordsDialogue250
100.0000%