Run: 2026-09-23-01M37PHST1WB90VNYBYP1JT6MW

Run Details

Duration:
19.0s
Cost:
$0.035260
Provider:
Claude Platform on AWS

Evaluation summary

Score Evaluator
Details Link
99.98% Matches word count (details)
98.40% Dialogue to Total Word Ratio (details)
99.1914% 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
"The Hendersons' kid turns seven Saturday," Molly said, unrolling a crayon map. "Forty guests. Forty presents." "Why is the map in crayon?" "I stole it from the kid. Authenticity, Bill." "Right. So how do we get in?" "We go as entertainment. I'm a magician. You're a clown." "Why am I the clown?" "Because you already own the shoes." "Those are orthopedic, Molly." "They're big and sad. Kids love big and sad. Now, while I pull a rabbit out of a hat, you load the presents into the van." "We don't have a rabbit." "We have a hamster. Nobody's counting ears." "And if someone notices forty presents vanishing?" "It's a magic show, Bill. That's the trick. They'll applaud." "What about the mums? Party mums are terrifying. They've got juice boxes and no mercy." "Distraction. You'll make balloon animals." "I can only make a snake." "Then you'll make forty snakes, slowly, with great confidence." "What's our getaway?" "The bouncy castle. We deflate it, hide inside, and roll." "That's not a plan. That's a nightmare with a pump." "Bill, every great heist starts as a nightmare." Bill sighed and adjusted his enormous shoes. "Does it end with prison?" "Only the bad ones. Pack the hamster."
created_at"2026-09-23T17:55:53.817Z" 9/23/2026, 5:55:53 PM
model"anthropic/claude-opus-5.5-20260921"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency5968
moderation_latency(null)
generation_time18964
tokens_prompt75
tokens_completion586
native_tokens_prompt95
native_tokens_completion1744
native_tokens_completion_images(null)
native_tokens_reasoning1261
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"end_turn"
service_tier"default"
usage0.03526
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790186153-5w3oMUm2nj1kSnhvE5wt"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790186153-PKbJnnlHcIZ8kNRgWZeF"
upstream_id"msg_011CfLoTMmC3LpJmx7JP9Ecq"
provider_responses
0
endpoint_id"3a2388bc-3740-4e64-a1f5-4e301726b6b9"
id"msg_011CfLoTMmC3LpJmx7JP9Ecq"
is_byokfalse
latency1837
model_permaslug"anthropic/claude-opus-5.5-20260921"
provider_name"Claude Platform on AWS"
status200
total_cost0.03526
cache_discount(null)
upstream_inference_cost0
provider_name"Claude Platform on AWS"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
99.98% Matches word count n/a
neededCleanfalse
words202
98.40% Dialogue to Total Word Ratio
Ratio: 93.56%, Deviation: 3.56%
neededCleanfalse
wordsTotal202
wordsDialogue189
99.1914%