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Run: 2026-10-27-01M5YES5QD3JQT794X7J6YKJHD
Run Details
Model:
GPT-6.1 Terra (Reasoning, Medium)
Test:
Dialogue tags
Scenario:
Write 500 words with 30% dialogue
Duration:
15.5s
Cost:
$0.005996
Provider:
OpenAI
Evaluation summary
Score
Evaluator
Details Link
0.00%
Matches word count
(details)
97.23%
Dialogue to Total Word Ratio
(details)
48.6150%
Overall
Model input
User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 30% 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, pinning its corners with a saltshaker, a sugar bowl, and two miniature jars of jam. The fourth corner stayed curled. She considered this an omen, then decided it was probably because the paper had been wrapped around a sausage roll. “The reconnaissance is complete. There are twelve presents, one inflatable castle, and a clown who keeps checking the sky like he owes it money.” “That’s Uncle Trevor. He’s not a clown. He’s in finance, and his face just does that.” Bill straightened the paper with a butter knife. The party was being held at his sister’s house, which gave him access to the garden gate, the kitchen door, and several years’ worth of complaints about the bathroom wallpaper. “The presents go on the table beside the cake. We wait until the candles are lit, then roll them out in a laundry cart.” “Why a laundry cart?” “Because a getaway car would attract attention in the kitchen.” Bill nodded. He had once tried to park a getaway car in a kitchen, and the resulting insurance paperwork had ended their brief experiment with legitimate employment. A waiter approached. Molly folded the plan over the words PRESENT ESCAPE ROUTE and ordered another tea. Bill ordered a slice of cake to familiarize himself with the enemy. It arrived covered in pink icing and little silver balls that bounced across the table whenever he tried to cut it. “I’ve got disguises. You’re the magician’s assistant, and I’m the magician, obviously.” “You can’t do magic.” “I can make twelve presents disappear. That’s essentially the whole profession.” Bill wiped icing from his chin and considered the photograph Molly had taken of the gifts. One was enormous and suspiciously bicycle-shaped. Another was a small envelope with his name on it, which meant his sister had also bought him a birthday card, although his birthday was in November. “The magician’s assistant usually gets sawed in half. I want that ruled out before we leave.” “Fine. No saws, no knives, no hurting anybody. We take the presents, not the children.” Molly tapped the photograph. Her employer had been specific: every present must be removed before four o’clock. He had also provided the key to a rented van and insisted that the thieves wear capes. Molly rarely questioned clients, but she had charged extra for the capes. Outside, a man in a glittering top hat appeared at the café window. He pressed a hand against the glass, produced a flower from his sleeve, and held up a note reading PLEASE HURRY. The magician had forgotten his wife’s birthday. The presents at the party were actually a surprise for her, bought by their daughter and hidden among the children’s coats. The laundry cart would take them to the van, which would take them to the restaurant where she was expecting a quiet dinner. “What if the birthday girl catches us?” “Then we improvise. That’s what the cape is for.” Bill looked again at the enormous present. The photograph showed handlebars protruding from one end and a gift tag addressed to his niece. He pointed it out to Molly. Molly crossed the bicycle off the plan. Bill crossed off the envelope too, just in case his sister had enclosed money.
created_at
"2026-10-27T10:34:02.358Z"
10/27/2026, 10:34:02 AM
model
"openai/gpt-6.1-terra-20261026"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
4189
moderation_latency
(null)
generation_time
15501
tokens_prompt
75
tokens_completion
1213
native_tokens_prompt
66
native_tokens_completion
1186
native_tokens_completion_images
0
native_tokens_reasoning
516
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
0.005996
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.1; linux; x64))"
http_referer
(null)
request_id
"req-1793097242-cxETwaF8ZqBkFv4PR9hi"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1793097242-YP42HiRE6IHmJybNKkxx"
upstream_id
"resp_074e1b0b2965b5a4016ae07e1a6ef887d1bc2f0d864aaf0ac2"
provider_responses
0
endpoint_id
"2d2ad10f-098e-4bbf-aa95-11f705b2b9a2"
id
"resp_074e1b0b2965b5a4016ae07e1a6ef887d1bc2f0d864aaf0ac2"
is_byok
false
latency
376
model_permaslug
"openai/gpt-6.1-terra-20261026"
provider_name
"OpenAI"
status
200
total_cost
0.005996
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
546
97.23%
Dialogue to Total Word Ratio
Ratio: 29.25%, Deviation: 0.75%
neededClean
false
wordsTotal
547
wordsDialogue
160
48.6150%