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Run: 2026-04-27-01KQ72K1VYJSAG8Y3WJ4HSZ33A
Run Details
Model:
Qwen 3.6 27B
Test:
Dialogue tags
Scenario:
Write 200 words with 90% dialogue
Duration:
1m 5s
Cost:
$0.014139
Provider:
Morph
Evaluation summary
Score
Evaluator
Details Link
27.17%
Matches word count
(details)
0.00%
Dialogue to Total Word Ratio
(details)
13.5829%
Overall
Model input
User/Human
You are a author of comedic heist books. Please write a 200 word scene that has 90% 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 creased map across the dashboard while Bill nervously clicked a pen, watching the suburban gates gleam in the bright afternoon sun. Wait until the cake is cut, slip through the doggy door. That dog has a personal trainer. Security is a golden retriever named Sir Barks a Lot. Excellent. Bypass hounds, loot, exit before the party game begins. The loot being plastic toys and three used bicycles? Plastic has a massive resale value. We hit the craft table and roll. What about kids? They are small, observant, and emotionally volatile. Dress as entertainers. I am a badger puppet, you are a damp jester. If they ask why we steal the gifts? We tell them it is a performance art piece about delayed gratification. Pack the net and stop sweating on the map. Fluorescents make me nervous. Your puppet smells like old carpet. It is vintage intimidation. Get in the van. Sir Barks a Lot naps at three fifteen. What if those deep naps go into overtime? Then we improvise. We do not share our snacks with the suspects.
created_at
"2026-04-27T08:58:41.414Z"
4/27/2026, 8:58:41 AM
model
"qwen/qwen3.6-27b-20260422"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
745
moderation_latency
(null)
generation_time
64501
tokens_prompt
77
tokens_completion
5363
native_tokens_prompt
76
native_tokens_completion
5874
native_tokens_completion_images
(null)
native_tokens_reasoning
5096
native_tokens_cached
64
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
"stop"
usage
0.0141394
router
(null)
provider_responses
0
endpoint_id
"826cab4e-dc26-4472-83be-e4ddd5ebd2ab"
id
"22c05e386ab749e2972ab1b557153bb8"
is_byok
false
latency
631
model_permaslug
"qwen/qwen3.6-27b-20260422"
provider_name
"Morph"
status
200
user_agent
"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer
(null)
request_id
"req-1777280321-bVdpzt1Ri6yVAHe2S1Wj"
session_id
(null)
api_type
"completions"
id
"gen-1777280321-FsHEIJuU2HmjlYIujaDG"
upstream_id
"22c05e386ab749e2972ab1b557153bb8"
total_cost
0.0141394
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Morph"
response_cache_source_id
(null)
Evaluation details
Result
Evaluator
Details
Meta Data
27.17%
Matches word count
n/a
neededClean
false
words
181
0.00%
Dialogue to Total Word Ratio
Ratio: 0.00%, Deviation: 90.00%
neededClean
false
wordsTotal
181
wordsDialogue
0
13.5829%