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Run: 2026-10-27-01M5YJH0E8YRB48GSEZM16ZR8S
Run Details
Model:
GPT-6.1 Terra (Reasoning, Medium)
Test:
Dialogue tags
Scenario:
Write 500 words with 30% dialogue
Duration:
13.0s
Cost:
$0.004451
Provider:
OpenAI
Evaluation summary
Score
Evaluator
Details Link
99.98%
Matches word count
(details)
51.08%
Dialogue to Total Word Ratio
(details)
75.5331%
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 blueprints across the bonnet of Bill’s car. They had been printed from the community centre’s website and featured a smiling cartoon caterpillar pointing towards the fire exits. Someone had drawn a moustache on the caterpillar. Bill inspected it with professional interest. “The party starts at two,” Molly said. “We go in at three, when the children are distracted by the magician.” Bill squinted at the plan. “Is he any good?” “Apparently he once made the mayor disappear.” “That sounds useful.” “Only for eight minutes. The mayor was under a table.” Bill had brought a toolkit, a thermos of tea and a carrier bag containing two false moustaches. Molly selected the larger one and held it beneath her nose. It made her look like a man who had been banned from several allotments. “We pose as entertainers,” she said. “You’re a clown. I’m your assistant.” “I don’t want to be a clown.” “Fine. You’re my assistant.” “That’s worse. The clown gets top billing.” They settled on balloon artists, largely because Bill already owned a pump and Molly could make a convincing sausage dog. Their disguises would get them through the front door, provided nobody asked for anything more elaborate than a sausage dog. Molly tapped a rectangle on the blueprint. “The presents will be here, beside the cake. We put them in the laundry trolley and wheel them out.” “Why would a party have a laundry trolley?” “It won’t. We’re bringing one.” Bill considered this. “That might attract attention.” “So would carrying forty presents in our arms.” He conceded the point. Molly had always been the brains of their operation, while Bill provided the muscle, the transport and, on one memorable occasion, a written apology to a goose. They had chosen the party after seeing an advertisement for it in the local paper: A MAGICAL AFTERNOON FOR EVERY CHILD IN TOWN. Molly estimated that such generosity would produce an impressive mountain of gifts. Bill had initially objected, until she explained that they would sell the presents and use the money to pay their overdue rent. “What if the children catch us?” he asked. “We’ll tell them we’re taking the presents somewhere safe.” “From whom?” Molly looked at him. “Obviously, from us.” Bill poured himself some tea and thought about that. Across the street, a little girl was attaching a handmade sign to the community centre railings. It read PLEASE BRING A PRESENT FOR A CHILD WHO DOESN’T HAVE ONE. He handed Molly his cup and went over to speak to her. When he returned, his expression had acquired the careful blankness it usually reserved for parking tickets. “The presents are for the children’s hospital,” he said. Molly folded the blueprint slowly. “Right. New plan.” “We rob the hospital instead?” “No, Bill. We buy a present.” “With what money?” She removed the false moustache and studied it. “We could sell the car.” Bill glanced at the car, whose passenger door was held shut with string. “We could buy a small present.”
created_at
"2026-10-27T11:39:29.164Z"
10/27/2026, 11:39:29 AM
model
"openai/gpt-6.1-terra-20261026"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
3899
moderation_latency
(null)
generation_time
12883
tokens_prompt
75
tokens_completion
818
native_tokens_prompt
66
native_tokens_completion
877
native_tokens_completion_images
0
native_tokens_reasoning
238
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
0.004451
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.22.1; linux; x64))"
http_referer
(null)
request_id
"req-1793101169-h15cva6rtVPFt4BXCSr8"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1793101169-mDLIn4fc8GL9WwoUHBFf"
upstream_id
"resp_0b5b26dc1d5fd3f8016ae08d7148e087d1a713bdb07085c359"
provider_responses
0
endpoint_id
"2d2ad10f-098e-4bbf-aa95-11f705b2b9a2"
id
"resp_0b5b26dc1d5fd3f8016ae08d7148e087d1a713bdb07085c359"
is_byok
false
latency
348
model_permaslug
"openai/gpt-6.1-terra-20261026"
provider_name
"OpenAI"
status
200
total_cost
0.004451
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
99.98%
Matches word count
n/a
neededClean
false
words
502
51.08%
Dialogue to Total Word Ratio
Ratio: 33.67%, Deviation: 3.67%
neededClean
false
wordsTotal
502
wordsDialogue
169
75.5331%