Run: 2026-04-24-01KPZTV761TKWAXM9D50XWW04D

Run Details

Duration:
7.5s
Cost:
$0.011640
Provider:
Amazon Bedrock

Evaluation summary

Score Evaluator
Details Link
99.92% Matches word count (details)
59.22% Dialogue to Total Word Ratio (details)
79.5716% 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 spread the blueprints across the card table, weighing the corners with half-empty cans of grape soda. The floor plan of the Peterson residence looked deceptively innocent, all sunrooms and mudrooms and a suspicious number of bathrooms for one family. Bill leaned over her shoulder, chewing a licorice rope with the grim focus of a man defusing a bomb. The party was Saturday. Tommy Peterson was turning seven, and according to the invitation Molly had steamed open at the mailbox, the theme was pirates. This detail delighted her enormously and troubled Bill deeply. Pirates meant eyepatches, and eyepatches meant depth perception problems, and depth perception problems meant he might trip over a toddler. "I hate toddlers," Bill muttered. Molly ignored him. She circled the back patio with a red marker, then drew an arrow toward the gift table, which she had labeled TREASURE in block letters. Thirty-two children had RSVP'd. Thirty-two children meant thirty-two gifts, minimum, and wealthy suburbanites always overspent out of competitive guilt. She tapped the marker against her teeth, calculating. A bounce house provided cover. A clown provided distraction. A piƱata provided chaos. Everything a working criminal could ask for, really, and cake besides.
created_at"2026-04-24T13:28:39.375Z" 4/24/2026, 1:28:39 PM
model"anthropic/claude-4.7-opus-20260416"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency634
moderation_latency(null)
generation_time7449
tokens_prompt77
tokens_completion325
native_tokens_prompt98
native_tokens_completion446
native_tokens_completion_images(null)
native_tokens_reasoning0
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"
usage0.01164
router(null)
provider_responses
0
endpoint_id"0fa65117-00d9-4835-808d-9b68041d9ce4"
id"e8595349-b992-43d9-8875-24b0c3859dc6"
is_byokfalse
latency634
model_permaslug"anthropic/claude-4.7-opus-20260416"
provider_name"Amazon Bedrock"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777037319-v4AkFmp3QZ2GiI36JYXe"
session_id(null)
api_type"completions"
id"gen-1777037319-1RxCObycah1megNOwRUO"
upstream_id"e8595349-b992-43d9-8875-24b0c3859dc6"
total_cost0.01164
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
99.92% Matches word count n/a
neededCleanfalse
words197
59.22% Dialogue to Total Word Ratio
Ratio: 1.49%, Deviation: 8.51%
neededCleanfalse
wordsTotal201
wordsDialogue3
79.5716%