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Run: 2026-09-03-01M1KRJ5A3PNKDH3J2QTP2DQ71
Run Details
Model:
Muse Glimmer 30B (Reasoning, Medium)
Test:
Dialogue tags
Scenario:
Write 200 words with 90% dialogue
Duration:
29.9s
Cost:
$0.001981
Provider:
Phala
Evaluation summary
Score
Evaluator
Details Link
100.00%
Matches word count
(details)
0.00%
Dialogue to Total Word Ratio
(details)
50.0000%
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 and Bill crouched behind the dumpster behind the community hall. The balloons were visible through the fence. Molly: Okay, plan is simple. We go in, grab the presents, get out. Bill: Simple? It's a kids' birthday party. There's glitter everywhere. Molly: Exactly. Parents are distracted by cake. Kids are distracted by sugar. Bill: What about the parents? Molly: They're busy taking photos. No one watches the gift table. Bill: And the presents? How many? Molly: Twenty-three. I counted from the window. Bill: Twenty-three presents for a six-year-old? That's excessive. Molly: That's why we're stealing them. We split them. Bill: I want the LEGO set. Molly: Fine, you get LEGO. I want the pink unicorn. Bill: Deal. What about the bouncy castle? Molly: We leave it. Too much work. Bill: And the piƱata? Molly: Already emptied. I checked. Bill: You're a genius. Molly: I'm a professional. Move at eight. Bill: Eight sharp, masks on, and no crying kids. Molly: If they cry, we give them a present. Reverse psychology. Bill: You're insane. Molly: I'm employed. Bill: Last time we stole from a kid, we got glitter in our shoes. Molly: Worth it. Bill: Okay, let's go. Molly: Wait, my cape.
created_at
"2026-09-03T13:50:32.266Z"
9/3/2026, 1:50:32 PM
model
"meta/muse-glimmer-30b-20260810"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
273
moderation_latency
(null)
generation_time
29821
tokens_prompt
75
tokens_completion
1550
native_tokens_prompt
118
native_tokens_completion
1796
native_tokens_completion_images
(null)
native_tokens_reasoning
1484
native_tokens_cached
117
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
0.00198058
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788443432-JSqfOjj8CjYaHB2DLw48"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788443432-2K2JskEKAicprt5RQYe1"
upstream_id
"req_b4ce7e353a127a0c53d7d56c16b7b8f3"
provider_responses
0
endpoint_id
"6244f10e-1e45-488b-a47f-f575e0edd12b"
id
"req_b4ce7e353a127a0c53d7d56c16b7b8f3"
is_byok
false
latency
230
model_permaslug
"meta/muse-glimmer-30b-20260810"
provider_name
"Phala"
status
200
total_cost
0.00198058
cache_discount
0.00003042
upstream_inference_cost
0
provider_name
"Phala"
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
0.00%
Dialogue to Total Word Ratio
Ratio: 1.47%, Deviation: 88.53%
neededClean
false
wordsTotal
204
wordsDialogue
3
50.0000%