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Run: 2026-09-02-01M1H5883EX3NWH3DBF2E9KKEF
Run Details
Model:
Z.AI GLM 5.3 Flash (Reasoning, Low)
Test:
Dialogue tags
Scenario:
Write 500 words with 50% dialogue
Duration:
30.9s
Cost:
$0.000182
Provider:
Z.AI
Evaluation summary
Score
Evaluator
Details Link
99.74%
Matches word count
(details)
0.00%
Dialogue to Total Word Ratio
(details)
49.8722%
Overall
Model input
User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 50% 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 blueprint across the hood of the van and tapped a crayon-drawn layout of a suburban backyard. Bill leaned in, chewing his toothpick. "Okay, walk me through it again," Bill said. "The target is a seven-year-old's birthday party." "Correct." "With ponies." "One pony. Keep up." Bill studied the diagram. "Why does the bounce house have a red circle around it?" "That's the vault. Presents go under the bounce house in a storage bin. I watched the mother do it during the last party on the block. Smart lady. Terrible opsec." "She put the gifts under an inflatable castle." "She put the gifts under an inflatable castle that requires a blower running twenty-four seven. Cut the power, the castle deflates, we've got a soft, quiet collapse and direct access." Bill nodded slowly. "That's actually clever." "I have my moments. Now, the guard schedule." "The guard schedule," Bill repeated. He pulled out his notebook. "There's a golden retriever named Biscuit. Sleeps on the patio. Wakes at the sound of sirens, doorbells, or the word 'treat.'" "You're kidding." "I did three days of surveillance, Molly. I know things about Biscuit." "Fine. We bribe him. I've got hot dogs in the cooler." "You're bribing a guard dog with hot dogs?" "Has it ever not worked?" Bill conceded this with a shrug. "And the humans? There's going to be thirty children and fifteen adults between us and that bin." "Which is why we go in costume." "Please don't say clown." "I'm saying clown." "Molly, I look terrifying in face paint. Kids cry when I wear regular clothes." "That's why you're not the clown. You're the balloon guy. Shirt, apron, pump, done. You twist a few animals, you create a diversion, I slide under the deflating castle." Bill groaned. "What kind of animals?" "Dogs. Kids love dogs." "Everything at this party is a dog. The guard's a dog. My cover is dog-themed. This job has a dog problem." "Every job has problems. That's why we're professionals." Molly rolled up the blueprint. "Timer starts when the cake comes out. Fifteen minutes of sugar chaos, nobody counts children, nobody notices a missing balloon guy." "And if the blower has a backup generator?" Molly paused. "Does it?" "How would I know? You're the one who did recon on the bounce house." "I did recon on the bounce house placement, not its electrical infrastructure. There's only so much a woman can learn from a hedge." "Great. So our entire exit strategy is 'hopefully the castle gets tired.'" "Bill. Bill. Look at me. We once stole a Fabergé egg from a man who kept a tiger. A tiger, Bill. You think we can't handle a deflating bouncy castle and one bribable retriever?" Bill was quiet for a moment, then smiled. "The tiger job. That was a good day." "Best day. Now get the apron. The party starts at two, and I want to be emotionally ready to paint a dolphin on my face by one-thirty." "You said dogs." "Dogs, dolphins. I contain multitudes."
created_at
"2026-09-02T13:34:35.768Z"
9/2/2026, 1:34:35 PM
model
"z-ai/glm-5.3-flash-20260826"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
4745
moderation_latency
(null)
generation_time
30786
tokens_prompt
75
tokens_completion
759
native_tokens_prompt
73
native_tokens_completion
705
native_tokens_completion_images
(null)
native_tokens_reasoning
0
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
0.000181725
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788356075-Kx27yOFPRfI0kvfPrIcR"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788356075-So26eaFe8KqPh1YHUByd"
upstream_id
"20260902213435a33b12c769a04ea9"
provider_responses
0
endpoint_id
"8e9fe48b-2f91-41c3-a8a7-e4a93a8c4ff0"
id
"20260902213435a33b12c769a04ea9"
is_byok
false
latency
4744
model_permaslug
"z-ai/glm-5.3-flash-20260826"
provider_name
"Z.AI"
status
200
total_cost
0.000181725
cache_discount
(null)
upstream_inference_cost
0
provider_name
"Z.AI"
response_cache_source_id
(null)
data_region
"global"
workspace_id
"97e315e5-d303-487d-83c1-83180e8a13d4"
Evaluation details
Result
Evaluator
Details
Meta Data
99.74%
Matches word count
n/a
neededClean
false
words
504
0.00%
Dialogue to Total Word Ratio
Ratio: 87.25%, Deviation: 37.25%
neededClean
false
wordsTotal
510
wordsDialogue
445
49.8722%