developer_uid: zonemercy
submission_id: chaiml-kimid-v1-cosine_v16
model_name: test
model_group: ChaiML/kimid-v1_cosine
status: inactive
timestamp: 2025-12-04T16:53:51+00:00
num_battles: 25278
num_wins: 12755
celo_rating: 1296.75
family_friendly_score: 0.5025999999999999
family_friendly_standard_error: 0.007070972210382389
submission_type: basic
model_repo: ChaiML/kimid-v1_cosine
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': 0.42552758972882443, 'latency_mean': 2.349952750205994, 'latency_p50': 2.3428598642349243, 'latency_p90': 2.5721471548080443}, {'batch_size': 2, 'throughput': 0.635367615917169, 'latency_mean': 3.141438454389572, 'latency_p50': 3.1554441452026367, 'latency_p90': 3.383943247795105}, {'batch_size': 3, 'throughput': 0.7744192285295366, 'latency_mean': 3.864527395963669, 'latency_p50': 3.8865572214126587, 'latency_p90': 4.236761498451233}, {'batch_size': 4, 'throughput': 0.8769339649638129, 'latency_mean': 4.549471825361252, 'latency_p50': 4.542629599571228, 'latency_p90': 5.016191005706786}, {'batch_size': 5, 'throughput': 0.9397572181899904, 'latency_mean': 5.30834908246994, 'latency_p50': 5.276513576507568, 'latency_p90': 6.016926336288452}]
gpu_counts: {'NVIDIA L40S': 1}
display_name: test
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: ChaiML/kimid-v1_cosine
model_size: 24B
ranking_group: single
throughput_3p7s: 0.75
us_pacific_date: 2025-12-04
win_ratio: 0.504588970646412
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>', 'User:', 'You:'], '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
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Running pipeline stage MKMLizer
Starting job with name chaiml-kimid-v1-cosine-v16-mkmlizer
Waiting for job on chaiml-kimid-v1-cosine-v16-mkmlizer to finish
chaiml-kimid-v1-cosine-v16-mkmlizer: bash: cannot set terminal process group (-1): Inappropriate ioctl for device
chaiml-kimid-v1-cosine-v16-mkmlizer: bash: no job control in this shell
chaiml-kimid-v1-cosine-v16-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-v1-cosine-v16-mkmlizer:   __import__('pkg_resources').declare_namespace(__name__)
chaiml-kimid-v1-cosine-v16-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-kimid-v1-cosine-v16-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  Version: 0.30.6+torch280                                           ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  belonging to:                                                      ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ║                                                                     ║
chaiml-kimid-v1-cosine-v16-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-kimid-v1-cosine-v16-mkmlizer: Downloaded to shared memory in 58.454s
chaiml-kimid-v1-cosine-v16-mkmlizer: Checking if ChaiML/kimid-v1_cosine already exists in ChaiML
chaiml-kimid-v1-cosine-v16-mkmlizer: quantizing model to /dev/shm/model_cache, profile:q4, folder:/tmp/tmp_3u9ao70, device:0
chaiml-kimid-v1-cosine-v16-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-kimid-v1-cosine-v16-mkmlizer: 
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chaiml-kimid-v1-cosine-v16-mkmlizer: The tokenizer you are loading from '/tmp/tmp_3u9ao70' 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-v1-cosine-v16-mkmlizer: quantized model in 276.692s
chaiml-kimid-v1-cosine-v16-mkmlizer: Processed model ChaiML/kimid-v1_cosine in 335.147s
chaiml-kimid-v1-cosine-v16-mkmlizer: creating bucket guanaco-mkml-models
chaiml-kimid-v1-cosine-v16-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-kimid-v1-cosine-v16-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia
chaiml-kimid-v1-cosine-v16-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia/config.json
chaiml-kimid-v1-cosine-v16-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia/special_tokens_map.json
chaiml-kimid-v1-cosine-v16-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia/tokenizer_config.json
chaiml-kimid-v1-cosine-v16-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia/tokenizer.json
chaiml-kimid-v1-cosine-v16-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia/flywheel_model.1.safetensors
chaiml-kimid-v1-cosine-v16-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-kimid-v1-cosine-v16/nvidia/flywheel_model.0.safetensors
Job chaiml-kimid-v1-cosine-v16-mkmlizer completed after 401.21s with status: succeeded
Stopping job with name chaiml-kimid-v1-cosine-v16-mkmlizer
Pipeline stage MKMLizer completed in 401.99s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-kimid-v1-cosine-v16
Waiting for inference service chaiml-kimid-v1-cosine-v16 to be ready
Tearing down inference service chaiml-kimid-v1-cosine-v16
%s, retrying in %s seconds...
Creating inference service chaiml-kimid-v1-cosine-v16
Waiting for inference service chaiml-kimid-v1-cosine-v16 to be ready
Inference service chaiml-kimid-v1-cosine-v16 ready after 170.81489491462708s
Pipeline stage MKMLDeployer completed in 343.25s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.26194167137146s
Received healthy response to inference request in 2.4840118885040283s
Received healthy response to inference request in 2.635465145111084s
Received healthy response to inference request in 2.312495231628418s
Received healthy response to inference request in 2.128445863723755s
5 requests
0 failed requests
5th percentile: 2.155145025253296
10th percentile: 2.181844186782837
20th percentile: 2.235242509841919
30th percentile: 2.2720523834228517
40th percentile: 2.2922738075256346
50th percentile: 2.312495231628418
60th percentile: 2.381101894378662
70th percentile: 2.4497085571289063
80th percentile: 2.5143025398254393
90th percentile: 2.5748838424682616
95th percentile: 2.605174493789673
99th percentile: 2.6294070148468016
mean time: 2.364471960067749
Pipeline stage StressChecker completed in 13.88s
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 1.14s
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 0.90s
Shutdown handler de-registered
chaiml-kimid-v1-cosine_v16 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
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
Generating Leaderboard row for %s
Generated Leaderboard row for %s
Pipeline stage OfflineFamilyFriendlyScorer completed in 4459.28s
Shutdown handler de-registered