NC Bench
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Run: 2026-09-02-01M1HA3JBV2D9HRW1KY695NHF9
Run Details
Model:
Qwen 3.8 Max (Reasoning, XHigh)
Test:
Dialogue tags
Scenario:
Write 200 words with 90% dialogue
Duration:
2m 25s
Cost:
$0.037994
Provider:
Alibaba
Evaluation summary
Score
Evaluator
Details Link
100.00%
Matches word count
(details)
36.79%
Dialogue to Total Word Ratio
(details)
68.3940%
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, I cannot wear another clown suit for this heist." "Bill, the children expect entertainment, and we expect their presents." "The bouncy castle entrance smells suspiciously like juice and despair." "Perfect. No parent investigates a fortress of sticky screaming joy." "I brought a sack, three balloons, and questionable moral judgment." "Excellent. We pose as entertainers, collect gifts, then vanish dramatically." "What if toddlers demand magic, Molly? I only have sandwiches." "Feed them sandwiches, Bill. Children consider lunch a spectacular miracle." "And the parents? They guard cake like tiny glittery dragons." "Distract them with glitter. Parents cannot resist sparkly emergency crafts." "I once lost an eyebrow to a birthday crafts incident." "That eyebrow was weak. Tonight we need focus, not eyebrows." "Fine. I will bag presents near the suspiciously crowded table." "Excellent. I will redirect cake enthusiasm toward the emergency balloon." "Molly, why is there a pony in your escape plan?" "The pony deserves presents too, Bill. Do not judge us." "If we are caught, I am blaming the birthday magician." "We are the birthday magicians, Bill. Commit to the sparkle." "Let us steal every present before the sugar crash strikes." "On three. Smile generously, Bill. Toddlers smell guilt and frosting."
created_at
"2026-09-02T14:59:25.209Z"
9/2/2026, 2:59:25 PM
model
"qwen/qwen3.8-max-20260803"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1610
moderation_latency
(null)
generation_time
144953
tokens_prompt
75
tokens_completion
5651
native_tokens_prompt
127
native_tokens_completion
6290
native_tokens_completion_images
(null)
native_tokens_reasoning
6006
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
0.037994
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788361165-4mtXaru0aMOkNQ2OoFDp"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788361165-ujy64sKQWC7HD9PHSNj9"
upstream_id
"chatcmpl-1a1a388d-cea6-96b8-a8b6-87eaf0fd4abc"
provider_responses
0
endpoint_id
"6332e9fd-e0c4-4cae-8c17-d25bc774864a"
id
"chatcmpl-1a1a388d-cea6-96b8-a8b6-87eaf0fd4abc"
is_byok
false
latency
1610
model_permaslug
"qwen/qwen3.8-max-20260803"
provider_name
"Alibaba"
status
200
total_cost
0.037994
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Alibaba"
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
36.79%
Dialogue to Total Word Ratio
Ratio: 100.00%, Deviation: 10.00%
neededClean
false
wordsTotal
200
wordsDialogue
200
68.3940%