developer_uid: chai_backend_admin
submission_id: chaiml-1025-quang-ir-lt_77106_v1
model_name: chaiml-1025-quang-ir-lt_77106_v1
model_group: ChaiML/1025-quang-ir-ltr
status: inactive
timestamp: 2025-10-25T20:51:17+00:00
num_battles: 6003
num_wins: 3172
celo_rating: 1290.49
family_friendly_score: 0.0
family_friendly_standard_error: 0.0
submission_type: basic
model_repo: ChaiML/1025-quang-ir-ltry-adjustment-ue-mem
model_architecture: MistralForCausalLM
model_num_parameters: 24096691200.0
best_of: 8
max_input_tokens: 2048
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.38505142487786775, 'latency_mean': 2.5969368696212767, 'latency_p50': 2.595895290374756, 'latency_p90': 2.832377219200134}, {'batch_size': 2, 'throughput': 0.576459577683612, 'latency_mean': 3.4693399262428284, 'latency_p50': 3.484502077102661, 'latency_p90': 3.791858673095703}, {'batch_size': 3, 'throughput': 0.7083755649906402, 'latency_mean': 4.220468555688858, 'latency_p50': 4.234263896942139, 'latency_p90': 4.762965655326843}, {'batch_size': 4, 'throughput': 0.8050942402238049, 'latency_mean': 4.946155433654785, 'latency_p50': 4.933034777641296, 'latency_p90': 5.497913146018981}, {'batch_size': 5, 'throughput': 0.8718385599642784, 'latency_mean': 5.7165942132472995, 'latency_p50': 5.691144108772278, 'latency_p90': 6.638064861297607}]
gpu_counts: {'NVIDIA L40S': 1}
display_name: chaiml-1025-quang-ir-lt_77106_v1
is_internal_developer: True
language_model: ChaiML/1025-quang-ir-ltry-adjustment-ue-mem
model_size: 24B
ranking_group: single
throughput_3p7s: 0.62
us_pacific_date: 2025-10-25
win_ratio: 0.5284024654339496
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>', '\n', 'You:', '####\n'], 'max_input_tokens': 2048, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s persona: {memory}", 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': 'You: {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-1025-quang-ir-lt-77106-v1-mkmlizer
Waiting for job on chaiml-1025-quang-ir-lt-77106-v1-mkmlizer to finish
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║                                                                     ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║                                                                     ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  Version: 0.30.2                                                    ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║                                                                     ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  belonging to:                                                      ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║                                                                     ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ║                                                                     ║
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: Downloaded to shared memory in 64.342s
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: Checking if ChaiML/1025-quang-ir-ltry-adjustment-ue-mem already exists in ChaiML
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpbgjras3h, device:0
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: quantized model in 42.333s
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: Processed model ChaiML/1025-quang-ir-ltry-adjustment-ue-mem in 106.675s
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: creating bucket guanaco-mkml-models
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia/config.json
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia/special_tokens_map.json
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia/tokenizer_config.json
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia/tokenizer.json
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia/flywheel_model.0.safetensors
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-1025-quang-ir-lt-77106-v1/nvidia/flywheel_model.1.safetensors
chaiml-1025-quang-ir-lt-77106-v1-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|          | 4/363 [00:00<00:14, 25.07it/s]
Loading 0:   2%|▏         | 7/363 [00:00<00:20, 17.10it/s]
Loading 0:   3%|▎         | 12/363 [00:00<00:14, 23.84it/s]
Loading 0:   4%|▍         | 15/363 [00:00<00:17, 20.23it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:14, 24.50it/s]
Loading 0:   6%|▌         | 22/363 [00:00<00:13, 25.86it/s]
Loading 0:   7%|▋         | 25/363 [00:01<00:12, 26.28it/s]
Loading 0:   9%|▉         | 32/363 [00:01<00:09, 36.45it/s]
Loading 0:  10%|▉         | 36/363 [00:01<00:14, 22.21it/s]
Loading 0:  11%|█         | 40/363 [00:01<00:12, 25.50it/s]
Loading 0:  12%|█▏        | 44/363 [00:01<00:11, 27.82it/s]
Loading 0:  13%|█▎        | 48/363 [00:01<00:10, 30.07it/s]
Loading 0:  14%|█▍        | 52/363 [00:01<00:10, 29.43it/s]
Loading 0:  16%|█▌        | 57/363 [00:02<00:09, 33.70it/s]
Loading 0:  17%|█▋        | 61/363 [00:02<00:09, 31.93it/s]
Loading 0:  18%|█▊        | 65/363 [00:02<00:08, 33.26it/s]
Loading 0:  19%|█▉        | 70/363 [00:02<00:10, 29.11it/s]
Loading 0:  20%|██        | 74/363 [00:02<00:11, 25.96it/s]
Loading 0:  22%|██▏       | 79/363 [00:02<00:09, 30.04it/s]
Loading 0:  23%|██▎       | 83/363 [00:02<00:08, 31.20it/s]
Loading 0:  24%|██▍       | 87/363 [00:03<00:10, 27.52it/s]
Loading 0:  25%|██▌       | 92/363 [00:03<00:10, 26.72it/s]
Loading 0:  27%|██▋       | 99/363 [00:03<00:07, 34.00it/s]
Loading 0:  28%|██▊       | 103/363 [00:03<00:08, 31.28it/s]
Loading 0:  29%|██▉       | 107/363 [00:03<00:09, 26.67it/s]
Loading 0:  31%|███       | 112/363 [00:03<00:08, 29.25it/s]
Loading 0:  32%|███▏      | 116/363 [00:04<00:08, 30.16it/s]
Loading 0:  33%|███▎      | 120/363 [00:04<00:07, 32.12it/s]
Loading 0:  34%|███▍      | 124/363 [00:04<00:07, 30.68it/s]
Loading 0:  36%|███▌      | 129/363 [00:04<00:06, 34.18it/s]
Loading 0:  37%|███▋      | 133/363 [00:04<00:07, 32.41it/s]
Loading 0:  38%|███▊      | 138/363 [00:04<00:06, 35.73it/s]
Loading 0:  39%|███▉      | 142/363 [00:04<00:06, 33.44it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:05, 39.90it/s]
Loading 0:  42%|████▏     | 154/363 [00:05<00:07, 26.95it/s]
Loading 0:  44%|████▎     | 158/363 [00:05<00:08, 24.92it/s]
Loading 0:  45%|████▌     | 165/363 [00:05<00:06, 32.04it/s]
Loading 0:  47%|████▋     | 169/363 [00:05<00:06, 31.04it/s]
Loading 0:  48%|████▊     | 174/363 [00:05<00:05, 33.49it/s]
Loading 0:  49%|████▉     | 178/363 [00:06<00:05, 32.11it/s]
Loading 0:  50%|█████     | 182/363 [00:06<00:05, 33.05it/s]
Loading 0:  52%|█████▏    | 187/363 [00:06<00:05, 29.83it/s]
Loading 0:  53%|█████▎    | 191/363 [00:06<00:05, 28.87it/s]
Loading 0:  54%|█████▎    | 195/363 [00:06<00:06, 26.13it/s]
Loading 0:  55%|█████▌    | 201/363 [00:19<02:14,  1.21it/s]
Loading 0:  56%|█████▌    | 203/363 [00:19<01:55,  1.39it/s]
Loading 0:  57%|█████▋    | 208/363 [00:19<01:13,  2.10it/s]
Loading 0:  58%|█████▊    | 211/363 [00:20<00:57,  2.65it/s]
Loading 0:  59%|█████▉    | 215/363 [00:20<00:39,  3.70it/s]
Loading 0:  60%|██████    | 218/363 [00:20<00:30,  4.72it/s]
Loading 0:  61%|██████    | 221/363 [00:20<00:23,  6.03it/s]
Loading 0:  62%|██████▏   | 224/363 [00:20<00:19,  7.26it/s]
Loading 0:  63%|██████▎   | 229/363 [00:20<00:12, 10.64it/s]
Loading 0:  64%|██████▍   | 232/363 [00:20<00:10, 12.59it/s]
Loading 0:  65%|██████▌   | 237/363 [00:20<00:07, 17.23it/s]
Loading 0:  66%|██████▋   | 241/363 [00:21<00:06, 19.69it/s]
Loading 0:  68%|██████▊   | 246/363 [00:21<00:04, 24.53it/s]
Loading 0:  69%|██████▉   | 250/363 [00:21<00:04, 25.60it/s]
Loading 0:  70%|███████   | 255/363 [00:21<00:03, 29.87it/s]
Loading 0:  71%|███████▏  | 259/363 [00:21<00:03, 29.41it/s]
Loading 0:  73%|███████▎  | 266/363 [00:21<00:02, 36.42it/s]
Loading 0:  75%|███████▍  | 271/363 [00:22<00:03, 26.05it/s]
Loading 0:  76%|███████▌  | 275/363 [00:22<00:03, 24.32it/s]
Loading 0:  78%|███████▊  | 282/363 [00:22<00:02, 31.50it/s]
Loading 0:  79%|███████▉  | 286/363 [00:22<00:02, 30.37it/s]
Loading 0:  80%|████████  | 291/363 [00:22<00:02, 33.65it/s]
Loading 0:  81%|████████▏ | 295/363 [00:22<00:02, 31.29it/s]
Loading 0:  82%|████████▏ | 299/363 [00:22<00:01, 32.36it/s]
Loading 0:  84%|████████▎ | 304/363 [00:23<00:01, 29.75it/s]
Loading 0:  85%|████████▍ | 308/363 [00:23<00:01, 28.95it/s]
Loading 0:  86%|████████▌ | 312/363 [00:23<00:01, 25.99it/s]
Loading 0:  88%|████████▊ | 318/363 [00:23<00:01, 31.69it/s]
Loading 0:  89%|████████▊ | 322/363 [00:23<00:01, 30.73it/s]
Loading 0:  90%|█████████ | 327/363 [00:23<00:01, 34.09it/s]
Loading 0:  91%|█████████ | 331/363 [00:23<00:01, 31.99it/s]
Loading 0:  92%|█████████▏| 335/363 [00:24<00:00, 33.14it/s]
Loading 0:  93%|█████████▎| 339/363 [00:24<00:00, 33.95it/s]
Loading 0:  94%|█████████▍| 343/363 [00:24<00:00, 20.40it/s]
Loading 0:  96%|█████████▌| 348/363 [00:24<00:00, 22.04it/s]
Loading 0:  98%|█████████▊| 355/363 [00:24<00:00, 29.61it/s]
Loading 0:  99%|█████████▉| 359/363 [00:24<00:00, 29.31it/s]
                                                            

Job chaiml-1025-quang-ir-lt-77106-v1-mkmlizer completed after 185.5s with status: succeeded
Stopping job with name chaiml-1025-quang-ir-lt-77106-v1-mkmlizer
Pipeline stage MKMLizer completed in 186.05s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.58s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-1025-quang-ir-lt-77106-v1
Waiting for inference service chaiml-1025-quang-ir-lt-77106-v1 to be ready
Inference service chaiml-1025-quang-ir-lt-77106-v1 ready after 90.8390896320343s
Pipeline stage MKMLDeployer completed in 91.82s
run pipeline stage %s
Running pipeline stage StressChecker
HTTPConnectionPool(host='guanaco-submitter.guanaco-backend.k2.chaiverse.com', port=80): Read timed out. (read timeout=20)
Received unhealthy response to inference request!
Received healthy response to inference request in 2.823068857192993s
Received healthy response to inference request in 2.192568063735962s
Received healthy response to inference request in 2.7002198696136475s
Received healthy response to inference request in 2.137051820755005s
5 requests
1 failed requests
5th percentile: 2.1481550693511964
10th percentile: 2.159258317947388
20th percentile: 2.1814648151397704
30th percentile: 2.294098424911499
40th percentile: 2.497159147262573
50th percentile: 2.7002198696136475
60th percentile: 2.749359464645386
70th percentile: 2.798499059677124
80th percentile: 6.286654996871951
90th percentile: 13.21382727622986
95th percentile: 16.67741341590881
99th percentile: 19.448282327651977
mean time: 5.998781633377075
%s, retrying in %s seconds...
Received healthy response to inference request in 2.7467939853668213s
Received healthy response to inference request in 2.6355597972869873s
Received healthy response to inference request in 2.142113208770752s
Received healthy response to inference request in 2.566934108734131s
Received healthy response to inference request in 2.0897133350372314s
5 requests
0 failed requests
5th percentile: 2.1001933097839354
10th percentile: 2.1106732845306397
20th percentile: 2.131633234024048
30th percentile: 2.2270773887634276
40th percentile: 2.3970057487487795
50th percentile: 2.566934108734131
60th percentile: 2.5943843841552736
70th percentile: 2.621834659576416
80th percentile: 2.657806634902954
90th percentile: 2.7023003101348877
95th percentile: 2.7245471477508545
99th percentile: 2.742344617843628
mean time: 2.4362228870391847
Pipeline stage StressChecker completed in 45.42s
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 0.62s
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 0.65s
Shutdown handler de-registered
chaiml-1025-quang-ir-lt_77106_v1 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.10s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.09s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service chaiml-1025-quang-ir-lt-77106-v1-profiler
Waiting for inference service chaiml-1025-quang-ir-lt-77106-v1-profiler to be ready
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
Pipeline stage OfflineFamilyFriendlyScorer completed in 5891.79s
Shutdown handler de-registered