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Run: 2026-04-27-01KQ74S188FXBY8TNNHYBVRYDT
Run Details
Model:
Qwen 3.6 35B
Test:
Dialogue tags
Scenario:
Write 200 words with 90% dialogue
Duration:
1m 21s
Cost:
$0.013028
Provider:
AtlasCloud
Evaluation summary
Score
Evaluator
Details Link
100.00%
Matches word count
(details)
100.00%
Dialogue to Total Word Ratio
(details)
100.0000%
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 adjusted her tactical tutu while Bill checked the laser pointer on the carpet. "Remember," Molly said, "the target is the wrapped chaos under the plastic tree." Bill nodded. "Right. The presents. All of them. Every single balloon animal and plastic spoon." "We move at three. When the piƱata drops, we sweep the gift pile." "What if a kid wakes up?" "We distract them with aggressively high-fived balloons and an off-key rendition of Happy Birthday." "And the escape?" "Down the slide. Into the laundry basket. Classic." "What about the security camera by the punch bowl?" "I will redirect it using a mirrored hubcap and a strategically thrown cookie." "Brilliant. Do we have the wheelbarrows?" "Packed with zip ties, velvet sacks, and emergency glitter." "I love how thorough you are." "I prefer professional. Now quiet. I hear bubble machines." "Time to ride. Let us steal some childhood joy." "Wait," Bill added. "Did we pack the noise-canceling headphones?" "Obviously. For the squeaky toys and the parent with the megaphone." "Perfect. Let us roll." "Make sure the grab-bags are lined." "Already double-confirmed. We take only the shiny stuff." "We secure the toys before the cake gets cut. Let us exit through the window."
created_at
"2026-04-27T09:36:54.543Z"
4/27/2026, 9:36:54 AM
model
"qwen/qwen3.6-35b-a3b-20260415"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
840
moderation_latency
(null)
generation_time
80758
tokens_prompt
77
tokens_completion
9411
native_tokens_prompt
76
native_tokens_completion
13484
native_tokens_completion_images
(null)
native_tokens_reasoning
13182
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
"stop"
usage
0.013027682
router
(null)
provider_responses
0
endpoint_id
"179c6985-3a1c-48f1-a009-9f3e3e402cdd"
id
"375db84c23324f6ea892f2620a935557"
is_byok
false
latency
840
model_permaslug
"qwen/qwen3.6-35b-a3b-20260415"
provider_name
"AtlasCloud"
status
200
user_agent
"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer
(null)
request_id
"req-1777282614-xBToap9ZjJauMEE9g6jQ"
session_id
(null)
api_type
"completions"
id
"gen-1777282614-sgptVNS6liX8MuZ3DCWk"
upstream_id
"375db84c23324f6ea892f2620a935557"
total_cost
0.013027682
cache_discount
(null)
upstream_inference_cost
0
provider_name
"AtlasCloud"
response_cache_source_id
(null)
Evaluation details
Result
Evaluator
Details
Meta Data
100.00%
Matches word count
n/a
neededClean
false
words
200
100.00%
Dialogue to Total Word Ratio
Ratio: 90.24%, Deviation: 0.24%
neededClean
false
wordsTotal
205
wordsDialogue
185
100.0000%