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Run: 2026-04-24-01KQ0GCMF5E5PRCKJ2R7MBD3GH
Run Details
Model:
Claude Opus 4.7 (Reasoning)
Test:
Dialogue tags
Scenario:
Write 500 words with 50% dialogue
Duration:
14.2s
Cost:
$0.026640
Provider:
Amazon Bedrock
Evaluation summary
Score
Evaluator
Details Link
1.04%
Matches word count
(details)
0.00%
Dialogue to Total Word Ratio
(details)
0.5180%
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
Messages
Meta
AI
The back booth of Denny's smelled like burnt coffee and regret, which Molly considered the perfect ambiance for criminal conspiracy. She unfolded a napkin covered in crayon diagrams across the table. "Okay, Bill. The target is a seven-year-old named Tanner Mackenzie. Birthday party Saturday at two. Bounce house, pony rides, and according to the Evite, a magician named Mr. Giggleworth." Bill squinted at the napkin. "Why does the bounce house have a skull on it?" "That's our extraction point." "Through the bounce house?" "Through the bounce house." Bill set down his fork. "Molly, I have robbed three banks, two armored cars, and the Cheesecake Factory on Lexington. I will not be deflating a bounce house full of children." "Nobody's deflating anything. We bounce out. It's a distraction." "It's a felony with cake." Molly stabbed a hash brown with surgical precision. "Listen. Tanner's dad is Derek Mackenzie. Hedge fund guy. Last year the kid got a PlayStation, a drone, and a savings bond worth more than your car." "My car isn't worth much." "Exactly. And this year the grandma is flying in from Connecticut with something in a Tiffany box. We clean house, we retire to Boca." Bill rubbed his temples. "We're stealing presents. From a child. A small child. With a Pokémon theme." "He's a rich child, Bill. He won't even notice. His parents will just buy him more. We're basically a life lesson." "I don't want to be a life lesson. I want to be a ghost in the wind." "You can be a ghost in the wind after we grab the Tiffany box." Bill exhaled through his nose the way he always did right before agreeing to something stupid. "What's my role?" Molly brightened. "You're Mr. Giggleworth." "Absolutely not." "I already paid the deposit." "Molly." "I already bought the costume." "Molly." "It has sequins, Bill. Sequins." Bill closed his eyes and appeared to pray to a god who had clearly stopped taking his calls. "And you?" "I'm the pony handler. I walk the pony around the yard, I case the gift table, I signal you during the dove trick." "There's a dove trick?" "There's a dove, and there's a trick. Whether they occur simultaneously depends on your commitment." He pointed his fork at her. "If one of those kids cries, I'm out." "Children at these parties don't cry. They're medicated and entitled. They'll barely look up from their juice pouches." "And the parents?" "Drinking mimosas in the kitchen. Derek's been having an affair with the neighbor, so the wife will be doing shots by one thirty." "You know a concerning amount about these people." Molly smiled and slid the napkin into her purse. "I'm thorough, Bill. That's why you love me." "I tolerate you." "Same thing, in this economy." She flagged the waitress. "Now eat up. We have a pony to rent."
created_at
"2026-04-24T19:45:10.121Z"
4/24/2026, 7:45:10 PM
model
"anthropic/claude-4.7-opus-20260416"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
695
moderation_latency
(null)
generation_time
14147
tokens_prompt
77
tokens_completion
754
native_tokens_prompt
98
native_tokens_completion
1046
native_tokens_completion_images
(null)
native_tokens_reasoning
0
native_tokens_cached
0
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
num_fetches
(null)
web_search_engine
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"end_turn"
usage
0.02664
router
(null)
provider_responses
0
endpoint_id
"0fa65117-00d9-4835-808d-9b68041d9ce4"
id
"4384cce5-dd0c-4497-af3a-6c2e7f24a0aa"
is_byok
false
latency
695
model_permaslug
"anthropic/claude-4.7-opus-20260416"
provider_name
"Amazon Bedrock"
status
200
user_agent
"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer
(null)
request_id
"req-1777059910-Z8VX6Of88VCR25FNmvZ0"
session_id
(null)
api_type
"completions"
id
"gen-1777059910-s3Ztavs28TeEbOmEikRU"
upstream_id
"4384cce5-dd0c-4497-af3a-6c2e7f24a0aa"
total_cost
0.02664
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Amazon Bedrock"
response_cache_source_id
(null)
Evaluation details
Result
Evaluator
Details
Meta Data
1.04%
Matches word count
n/a
neededClean
false
words
474
0.00%
Dialogue to Total Word Ratio
Ratio: 77.31%, Deviation: 27.31%
neededClean
false
wordsTotal
476
wordsDialogue
368
0.5180%