developer_uid: zmeeks
submission_id: mistralai-mistral-nem_93303_v501
model_name: nemo-v0307
model_group: mistralai/Mistral-Nemo-I
status: torndown
timestamp: 2025-06-28T09:52:48+00:00
num_battles: 6562
num_wins: 2939
celo_rating: 1231.01
family_friendly_score: 0.6396
family_friendly_standard_error: 0.006789872458301407
submission_type: basic
model_repo: mistralai/Mistral-Nemo-Instruct-2407
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.5994209406017452, 'latency_mean': 1.6681559443473817, 'latency_p50': 1.664722204208374, 'latency_p90': 1.8357943058013915}, {'batch_size': 3, 'throughput': 1.085219258454447, 'latency_mean': 2.747381283044815, 'latency_p50': 2.7576483488082886, 'latency_p90': 3.0527955055236817}, {'batch_size': 5, 'throughput': 1.297743230758101, 'latency_mean': 3.8393392741680143, 'latency_p50': 3.8676929473876953, 'latency_p90': 4.245905184745789}, {'batch_size': 6, 'throughput': 1.3713328677580459, 'latency_mean': 4.349883422851563, 'latency_p50': 4.404808521270752, 'latency_p90': 4.860770583152771}, {'batch_size': 8, 'throughput': 1.4355359551675118, 'latency_mean': 5.542345349788666, 'latency_p50': 5.518802165985107, 'latency_p90': 6.294594430923461}, {'batch_size': 10, 'throughput': 1.4579737216086215, 'latency_mean': 6.792182763814926, 'latency_p50': 6.755640506744385, 'latency_p90': 7.632172179222107}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: nemo-v0307
is_internal_developer: False
language_model: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
ranking_group: single
throughput_3p7s: 1.28
us_pacific_date: 2025-06-28
win_ratio: 0.4478817433709235
generation_params: {'temperature': 0.3, 'top_p': 0.7, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': '### Instruction:\n{memory}\n', 'prompt_template': '### Input:\n{prompt}\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '### Response:\n{bot_name}:', 'truncate_by_message': False}
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 mistralai-mistral-nem-93303-v501-mkmlizer
Waiting for job on mistralai-mistral-nem-93303-v501-mkmlizer to finish
mistralai-mistral-nem-93303-v501-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nem-93303-v501-mkmlizer: ║                                                                     ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║                                                                     ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  Version: 0.29.3                                                    ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  https://mk1.ai                                                     ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║                                                                     ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  belonging to:                                                      ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║                                                                     ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
mistralai-mistral-nem-93303-v501-mkmlizer: ║                                                                     ║
mistralai-mistral-nem-93303-v501-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nem-93303-v501-mkmlizer: Downloaded to shared memory in 46.404s
mistralai-mistral-nem-93303-v501-mkmlizer: Checking if mistralai/Mistral-Nemo-Instruct-2407 already exists in ChaiML
mistralai-mistral-nem-93303-v501-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpr6_ynmcn, device:0
mistralai-mistral-nem-93303-v501-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nem-93303-v501-mkmlizer: quantized model in 30.094s
mistralai-mistral-nem-93303-v501-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 76.581s
mistralai-mistral-nem-93303-v501-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nem-93303-v501-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nem-93303-v501-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v501
mistralai-mistral-nem-93303-v501-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v501/config.json
mistralai-mistral-nem-93303-v501-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v501/special_tokens_map.json
mistralai-mistral-nem-93303-v501-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v501/tokenizer_config.json
mistralai-mistral-nem-93303-v501-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v501/tokenizer.json
mistralai-mistral-nem-93303-v501-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v501/flywheel_model.0.safetensors
mistralai-mistral-nem-93303-v501-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:11, 31.69it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:06, 50.50it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:07, 43.67it/s]
Loading 0:   7%|▋         | 24/363 [00:00<00:07, 42.87it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:06, 48.57it/s]
Loading 0:  10%|█         | 37/363 [00:00<00:07, 44.65it/s]
Loading 0:  12%|█▏        | 42/363 [00:00<00:07, 43.27it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:06, 48.15it/s]
Loading 0:  15%|█▌        | 55/363 [00:01<00:06, 44.56it/s]
Loading 0:  17%|█▋        | 61/363 [00:01<00:08, 34.35it/s]
Loading 0:  18%|█▊        | 65/363 [00:01<00:08, 33.44it/s]
Loading 0:  20%|█▉        | 72/363 [00:01<00:07, 39.69it/s]
Loading 0:  21%|██        | 77/363 [00:01<00:06, 41.82it/s]
Loading 0:  23%|██▎       | 82/363 [00:02<00:07, 35.32it/s]
Loading 0:  25%|██▍       | 89/363 [00:02<00:06, 42.52it/s]
Loading 0:  26%|██▌       | 94/363 [00:02<00:06, 42.60it/s]
Loading 0:  27%|██▋       | 99/363 [00:02<00:06, 43.28it/s]
Loading 0:  29%|██▊       | 104/363 [00:02<00:05, 44.78it/s]
Loading 0:  30%|███       | 110/363 [00:02<00:06, 41.92it/s]
Loading 0:  32%|███▏      | 115/363 [00:02<00:05, 42.67it/s]
Loading 0:  33%|███▎      | 120/363 [00:02<00:05, 40.75it/s]
Loading 0:  34%|███▍      | 125/363 [00:02<00:05, 42.73it/s]
Loading 0:  36%|███▌      | 130/363 [00:03<00:05, 42.46it/s]
Loading 0:  37%|███▋      | 135/363 [00:03<00:05, 42.25it/s]
Loading 0:  39%|███▊      | 140/363 [00:03<00:05, 43.53it/s]
Loading 0:  40%|███▉      | 145/363 [00:03<00:07, 27.35it/s]
Loading 0:  41%|████      | 149/363 [00:03<00:07, 28.06it/s]
Loading 0:  43%|████▎     | 156/363 [00:03<00:05, 35.50it/s]
Loading 0:  44%|████▍     | 161/363 [00:04<00:05, 37.18it/s]
Loading 0:  46%|████▌     | 166/363 [00:04<00:05, 38.98it/s]
Loading 0:  47%|████▋     | 171/363 [00:04<00:04, 41.21it/s]
Loading 0:  48%|████▊     | 176/363 [00:04<00:05, 34.72it/s]
Loading 0:  50%|█████     | 183/363 [00:04<00:04, 42.04it/s]
Loading 0:  52%|█████▏    | 188/363 [00:04<00:04, 42.09it/s]
Loading 0:  53%|█████▎    | 193/363 [00:04<00:04, 41.52it/s]
Loading 0:  55%|█████▍    | 198/363 [00:04<00:03, 43.45it/s]
Loading 0:  56%|█████▌    | 203/363 [00:05<00:04, 36.54it/s]
Loading 0:  58%|█████▊    | 210/363 [00:05<00:03, 43.15it/s]
Loading 0:  59%|█████▉    | 215/363 [00:05<00:03, 43.42it/s]
Loading 0:  61%|██████    | 221/363 [00:05<00:03, 46.98it/s]
Loading 0:  62%|██████▏   | 226/363 [00:05<00:04, 29.81it/s]
Loading 0:  63%|██████▎   | 230/363 [00:05<00:04, 30.10it/s]
Loading 0:  65%|██████▌   | 237/363 [00:05<00:03, 37.73it/s]
Loading 0:  67%|██████▋   | 242/363 [00:06<00:03, 39.25it/s]
Loading 0:  68%|██████▊   | 247/363 [00:06<00:02, 40.73it/s]
Loading 0:  69%|██████▉   | 252/363 [00:06<00:02, 42.56it/s]
Loading 0:  71%|███████   | 257/363 [00:06<00:03, 35.09it/s]
Loading 0:  73%|███████▎  | 264/363 [00:06<00:02, 42.52it/s]
Loading 0:  74%|███████▍  | 269/363 [00:06<00:02, 42.90it/s]
Loading 0:  75%|███████▌  | 274/363 [00:06<00:02, 43.05it/s]
Loading 0:  77%|███████▋  | 279/363 [00:06<00:01, 43.06it/s]
Loading 0:  78%|███████▊  | 284/363 [00:07<00:02, 34.94it/s]
Loading 0:  80%|████████  | 291/363 [00:07<00:01, 41.85it/s]
Loading 0:  82%|████████▏ | 296/363 [00:07<00:01, 42.51it/s]
Loading 0:  83%|████████▎ | 301/363 [00:07<00:01, 44.04it/s]
Loading 0:  84%|████████▍ | 306/363 [00:07<00:02, 24.27it/s]
Loading 0:  85%|████████▌ | 310/363 [00:08<00:02, 25.42it/s]
Loading 0:  87%|████████▋ | 314/363 [00:08<00:01, 27.71it/s]
Loading 0:  88%|████████▊ | 320/363 [00:08<00:01, 33.47it/s]
Loading 0:  90%|████████▉ | 326/363 [00:08<00:01, 35.28it/s]
Loading 0:  91%|█████████ | 331/363 [00:08<00:00, 36.79it/s]
Loading 0:  93%|█████████▎| 338/363 [00:08<00:00, 42.54it/s]
Loading 0:  94%|█████████▍| 343/363 [00:08<00:00, 44.28it/s]
Loading 0:  96%|█████████▌| 348/363 [00:08<00:00, 37.43it/s]
Loading 0:  98%|█████████▊| 355/363 [00:09<00:00, 44.19it/s]
Loading 0:  99%|█████████▉| 360/363 [00:09<00:00, 43.92it/s]
                                                            

Job mistralai-mistral-nem-93303-v501-mkmlizer completed after 105.23s with status: succeeded
Stopping job with name mistralai-mistral-nem-93303-v501-mkmlizer
Pipeline stage MKMLizer completed in 105.75s
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 mistralai-mistral-nem-93303-v501
Waiting for inference service mistralai-mistral-nem-93303-v501 to be ready
Inference service mistralai-mistral-nem-93303-v501 ready after 160.55501508712769s
Pipeline stage MKMLDeployer completed in 161.29s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.722435712814331s
Received healthy response to inference request in 1.5444691181182861s
Received healthy response to inference request in 2.63183856010437s
Received healthy response to inference request in 1.6933410167694092s
Received healthy response to inference request in 1.601505994796753s
5 requests
0 failed requests
5th percentile: 1.5558764934539795
10th percentile: 1.5672838687896729
20th percentile: 1.5900986194610596
30th percentile: 1.6198729991912841
40th percentile: 1.6566070079803468
50th percentile: 1.6933410167694092
60th percentile: 2.0687400341033935
70th percentile: 2.4441390514373778
80th percentile: 2.6499579906463624
90th percentile: 2.6861968517303465
95th percentile: 2.704316282272339
99th percentile: 2.7188118267059327
mean time: 2.03871808052063
Pipeline stage StressChecker completed in 11.81s
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 0.71s
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 0.77s
Shutdown handler de-registered
mistralai-mistral-nem_93303_v501 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
Pipeline stage OfflineFamilyFriendlyScorer completed in 3300.38s
Shutdown handler de-registered
mistralai-mistral-nem_93303_v501 status is now inactive due to auto deactivation removed underperforming models
mistralai-mistral-nem_93303_v501 status is now torndown due to DeploymentManager action