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Run: 2026-10-27-01M5YH7EMM6Z6ZFRQ70J71HNZK
Run Details
Model:
GPT-6.1 Terra (Reasoning, Medium)
Test:
Dialogue tags
Scenario:
Write 500 words with 70% dialogue
Duration:
14.2s
Cost:
$0.006016
Provider:
OpenAI
Evaluation summary
Score
Evaluator
Details Link
0.00%
Matches word count
(details)
65.13%
Dialogue to Total Word Ratio
(details)
32.5674%
Overall
Model input
User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 70% 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
Molly spread the floor plan across the café table, weighting its corners with sugar packets. Bill studied the crayon drawing of a house, a garden, and something labeled ME. “That’s the birthday boy,” Molly said. “The presents will be in the conservatory until cake. We go in during the magician’s finale, take every last one, and leave.” Bill squinted at the picture. “Is the magician any good?” “According to the reviews, he once made a rabbit disappear for three days. By the time it came back, everyone had gone home.” “So we’ve got three days?” “We’ve got six minutes. The rabbit thing was an accident, and his insurance company is still involved. Try to focus on the presents.” Bill took a notebook from his coat. Its cover read MY CRIMES, with the word CRIMES crossed out and replaced by HOLIDAYS. “Entry point?” he asked. “The side gate. I’ll bring bolt cutters.” “Bit dramatic for a children’s party, isn’t it?” “Fine. I’ll bring the key. I got it from the family’s cleaner.” “You didn’t say we had an inside person.” “We don’t. She dropped it outside the bakery and I picked it up. I’m going to put it back afterwards, so write that down too.” Bill wrote KEY: BORROWED, underlining it twice. “And the children?” he asked. “They’ll notice two strangers carrying their presents away, especially if I have to make two trips.” “They’ll be busy watching the magician. We’ll wear matching polo shirts, so any adult who spots us will assume we work for the party company.” “Which company?” “Happy Hippo Events. They’re delivering the bouncy castle at eleven. I rang them and told them the party had been moved to Sunday.” Bill looked impressed. “And they believed you?” “No, so I booked the castle for Sunday as well. It was expensive, but at least we’ll have somewhere to celebrate.” She slid a photograph across the table. The conservatory door stood open behind a stack of brightly wrapped boxes. “Big haul,” Bill said. “What if one of them’s a pony?” “In that box?” “A small pony. Or a voucher for one. My aunt gave me a pony voucher when I was eight, and it turned out to be a photograph of her horse.” Molly studied the picture. “Put the biggest boxes in the van first. Then come back for the little ones. I’ll keep watch by the gate.” “Why don’t you carry anything?” “Because I’m the lookout.” “And if somebody sees you?” “I’ll say I’m waiting for Happy Hippo Events. If somebody sees you, put the boxes down and pretend you’re rearranging them.” Bill made a note. “What if a child asks me to open one?” “Tell them they have to wait for their parents.” “What if their parents ask?” “Tell them they have to wait for the child.” Bill closed his notebook. Outside, a delivery van passed with a grinning pink hippopotamus painted on its side. “That reminds me,” he said. “What are we doing with the presents?” “Selling them.” “All of them?” Molly nodded. “Even the pony voucher?” “We’ll discuss the pony voucher when we find it.” Bill paid for their coffees. On the way out, he bought a birthday card and signed it Sorry about the rabbit, just in case.
created_at
"2026-10-27T11:16:47.391Z"
10/27/2026, 11:16:47 AM
model
"openai/gpt-6.1-terra-20261026"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
6803
moderation_latency
(null)
generation_time
14200
tokens_prompt
75
tokens_completion
998
native_tokens_prompt
66
native_tokens_completion
1190
native_tokens_completion_images
0
native_tokens_reasoning
473
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
"completed"
service_tier
"default"
usage
0.006016
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.1; linux; x64))"
http_referer
(null)
request_id
"req-1793099807-wEpLPgdlzhs33B21tEKU"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1793099807-xLhkGXRZVM5h8bcuwKVT"
upstream_id
"resp_097079dbbd1b0e0e016ae0881f916087d1afe1ab2770e57459"
provider_responses
0
endpoint_id
"2d2ad10f-098e-4bbf-aa95-11f705b2b9a2"
id
"resp_097079dbbd1b0e0e016ae0881f916087d1afe1ab2770e57459"
is_byok
false
latency
433
model_permaslug
"openai/gpt-6.1-terra-20261026"
provider_name
"OpenAI"
status
200
total_cost
0.006016
cache_discount
(null)
upstream_inference_cost
0
provider_name
"OpenAI"
response_cache_source_id
(null)
data_region
"global"
workspace_id
"97e315e5-d303-487d-83c1-83180e8a13d4"
Evaluation details
Result
Evaluator
Details
Meta Data
0.00%
Matches word count
n/a
neededClean
false
words
543
65.13%
Dialogue to Total Word Ratio
Ratio: 72.93%, Deviation: 2.93%
neededClean
false
wordsTotal
543
wordsDialogue
396
32.5674%