developer_uid: zonemercy
submission_id: chaiml-kimid-v2-cosine-_80852_v4
model_name: test
model_group: ChaiML/kimid-v2_cosine-l
status: inactive
timestamp: 2025-12-04T23:17:06+00:00
num_battles: 5700
num_wins: 2968
celo_rating: 1305.9
family_friendly_score: 0.507
family_friendly_standard_error: 0.007070374813261317
submission_type: basic
model_repo: ChaiML/kimid-v2_cosine-lr2e6g16
model_architecture: MistralForCausalLM
model_num_parameters: 24096691200.0
best_of: 8
max_input_tokens: 2048
max_output_tokens: 72
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.421933745358256, 'latency_mean': 2.3699763572216033, 'latency_p50': 2.3826839923858643, 'latency_p90': 2.5629120588302614}, {'batch_size': 2, 'throughput': 0.6283016716347524, 'latency_mean': 3.1806976687908173, 'latency_p50': 3.1874195337295532, 'latency_p90': 3.4208820343017576}, {'batch_size': 3, 'throughput': 0.7664694987908449, 'latency_mean': 3.904179105758667, 'latency_p50': 3.8828428983688354, 'latency_p90': 4.278353023529053}, {'batch_size': 4, 'throughput': 0.8564111689990487, 'latency_mean': 4.652549653053284, 'latency_p50': 4.655846834182739, 'latency_p90': 5.39890410900116}, {'batch_size': 5, 'throughput': 0.9155374336035721, 'latency_mean': 5.439590069055558, 'latency_p50': 5.453068256378174, 'latency_p90': 6.155188655853271}]
gpu_counts: {'NVIDIA L40S': 1}
display_name: test
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: ChaiML/kimid-v2_cosine-lr2e6g16
model_size: 24B
ranking_group: single
throughput_3p7s: 0.73
us_pacific_date: 2025-12-04
win_ratio: 0.5207017543859649
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['</s>', 'You:', 'User:'], 'max_input_tokens': 2048, 'best_of': 8, 'max_output_tokens': 72}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '####\n{bot_name}:', 'truncate_by_message': True}
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name chaiml-kimid-v2-cosine-80852-v4-mkmlizer
Waiting for job on chaiml-kimid-v2-cosine-80852-v4-mkmlizer to finish
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: bash: no job control in this shell
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: /root/miniconda3/envs/nvidia/lib/python3.11/site-packages/mk1/__init__.py:1: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
chaiml-kimid-v2-cosine-80852-v4-mkmlizer:   __import__('pkg_resources').declare_namespace(__name__)
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  Version: 0.30.6+torch280                                           ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  belonging to:                                                      ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ║                                                                     ║
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: Downloaded to shared memory in 43.742s
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: Checking if ChaiML/kimid-v2_cosine-lr2e6g16 already exists in ChaiML
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmpdcqhkf58, device:0
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: 
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chaiml-kimid-v2-cosine-80852-v4-mkmlizer: The tokenizer you are loading from '/tmp/tmpdcqhkf58' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue.
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: quantized model in 276.631s
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: Processed model ChaiML/kimid-v2_cosine-lr2e6g16 in 320.374s
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: creating bucket guanaco-mkml-models
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-kimid-v2-cosine-80852-v4/nvidia
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-kimid-v2-cosine-80852-v4/nvidia/tokenizer.json
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-kimid-v2-cosine-80852-v4/nvidia/flywheel_model.1.safetensors
chaiml-kimid-v2-cosine-80852-v4-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-kimid-v2-cosine-80852-v4/nvidia/flywheel_model.0.safetensors
Job chaiml-kimid-v2-cosine-80852-v4-mkmlizer completed after 378.55s with status: succeeded
Stopping job with name chaiml-kimid-v2-cosine-80852-v4-mkmlizer
Pipeline stage MKMLizer completed in 379.04s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.15s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-kimid-v2-cosine-80852-v4
Waiting for inference service chaiml-kimid-v2-cosine-80852-v4 to be ready
Inference service chaiml-kimid-v2-cosine-80852-v4 ready after 181.12692975997925s
Pipeline stage MKMLDeployer completed in 181.63s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.3960347175598145s
Received healthy response to inference request in 2.2199411392211914s
Received healthy response to inference request in 2.0955872535705566s
Received healthy response to inference request in 3.0034074783325195s
Received healthy response to inference request in 2.2073261737823486s
5 requests
0 failed requests
5th percentile: 2.117935037612915
10th percentile: 2.1402828216552736
20th percentile: 2.18497838973999
30th percentile: 2.209849166870117
40th percentile: 2.214895153045654
50th percentile: 2.2199411392211914
60th percentile: 2.2903785705566406
70th percentile: 2.36081600189209
80th percentile: 2.5175092697143557
90th percentile: 2.7604583740234374
95th percentile: 2.8819329261779782
99th percentile: 2.9791125679016113
mean time: 2.384459352493286
Pipeline stage StressChecker completed in 13.19s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.63s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 0.62s
Shutdown handler de-registered
chaiml-kimid-v2-cosine-_80852_v4 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Generating Leaderboard row for %s
Generated Leaderboard row for %s
Pipeline stage OfflineFamilyFriendlyScorer completed in 2562.56s
Shutdown handler de-registered
chaiml-kimid-v2-cosine-_80852_v4 status is now inactive due to auto deactivation removed underperforming models