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Run: 2026-09-03-01M1KY8GZY3GJ87BSF85DSA2AG
Run Details
Model:
Qwen 3.8 27B (Reasoning, XHigh)
Test:
Dialogue tags
Scenario:
Write 200 words with 10% dialogue
Duration:
1m 57s
Cost:
$0.023635
Provider:
AkashML
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 10% 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 party hat, a tiny foil crown that made her look like suspicious royalty outside the birthday party. Bill crouched beside the swaying banner, its letters dancing in the fan breeze while he nervously planned the entry path. Molly whispered, "Bill, all presents are inside," while pointing her ribbon gun at the biggest box with a red bow. Bill replied, "Molly, we need balloons," then checked the punch bowl for hidden cameras and shiny spoons and forks too. Molly nodded, "We take all presents after cake," then patted her apron pockets for candy wrapper evidence and gum sticks. Bill grinned, "Then we vanish into punch," and lifted a toy forklift that belonged to a suspicious little party track. The children sang a song about sharing, which sounded like a very polite threat to professional criminals on the run. Molly winked at the clown, who inflated a giant balloon that looked ready to become a very useful witness soon. Bill grabbed the forklift, tucked it under his arm, and pretended to be an uncle with strong opinions about toys. The night smelled of frosting, stolen joy, and one very suspicious plastic truck rolling away toward the dark parking lot.
created_at
"2026-09-03T15:30:08.005Z"
9/3/2026, 3:30:08 PM
model
"qwen/qwen3.8-27b-20260814"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
300
moderation_latency
(null)
generation_time
116912
tokens_prompt
75
tokens_completion
7999
native_tokens_prompt
118
native_tokens_completion
9439
native_tokens_completion_images
(null)
native_tokens_reasoning
7702
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"
service_tier
(null)
usage
0.02363526
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788449408-LgVruiK8OZXyBvnkrjDr"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788449408-4VtN6IzCTzMJiztrBdxB"
upstream_id
"chatcmpl-866cf00789fbf0db"
provider_responses
0
endpoint_id
"c15e008c-6180-4155-8707-bde541bc7884"
id
"chatcmpl-866cf00789fbf0db"
is_byok
false
latency
300
model_permaslug
"qwen/qwen3.8-27b-20260814"
provider_name
"AkashML"
status
200
total_cost
0.02363526
cache_discount
(null)
upstream_inference_cost
0
provider_name
"AkashML"
response_cache_source_id
(null)
data_region
"global"
workspace_id
"97e315e5-d303-487d-83c1-83180e8a13d4"
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: 10.00%, Deviation: 0.00%
neededClean
false
wordsTotal
200
wordsDialogue
20
100.0000%