chaiml-bol-v5-opusdv1b-_56373

developer_uid: zonemercy
submission_id: chaiml-bol-v5-opusdv1b-_56373_v1
model_name: chaiml-bol-v5-opusdv1b-_56373_v1
model_group: ChaiML/bol-v5-opusdv1b-l
status: torndown
timestamp: 2026-02-06T18:23:19+00:00
num_battles: 11787
num_wins: 6303
celo_rating: 1327.88
family_friendly_score: 0.5648
family_friendly_standard_error: 0.007011432949119602
submission_type: basic
model_repo: ChaiML/bol-v5-opusdv1b-lr1e5ep2r64g4b01
model_architecture: Qwen3MoeForCausalLM
model_num_parameters: 18790207488.0
best_of: 8
max_input_tokens: 2048
max_output_tokens: 72
reward_model: chaiml-prm-kimi-v1-300k_92220_v7
display_name: chaiml-bol-v5-opusdv1b-_56373_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: ChaiML/bol-v5-opusdv1b-lr1e5ep2r64g4b01
model_size: 19B
ranking_group: single
us_pacific_date: 2026-02-03
win_ratio: 0.534741664545686
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['<|assistant|>', '<|user|>', '####', '</think>', '</s>', '<|im_end|>'], 'max_input_tokens': 2048, 'best_of': 8, 'max_output_tokens': 72}
formatter: {'memory_template': "<|im_start|>system\n{bot_name}'s persona: {memory}<|im_end|>\n", 'prompt_template': '', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{bot_name}:', 'truncate_by_message': True}
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
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Running pipeline stage VLLMUploader
Starting job with name chaiml-bol-v5-opusdv1b-56373-v1-uploader
Waiting for job on chaiml-bol-v5-opusdv1b-56373-v1-uploader to finish
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Using quantization_mode: w4a16
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Checking if ChaiML/bol-v5-opusdv1b-lr1e5ep2r64g4b01-W4A16 already exists in ChaiML
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Downloading snapshot of ChaiML/bol-v5-opusdv1b-lr1e5ep2r64g4b01...
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: Downloaded in 213.792s
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Applying quantization...
chaiml-bol-v5-opusdv1b-56373-v1-uploader: [33;1m2026-02-03 06:39:02 WARNING modeling_utils.py L4670: `torch_dtype` is deprecated! Use `dtype` instead![0m
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: [38;20m2026-02-03 06:39:17 INFO base.py L366: using torch.bfloat16 for quantization tuning[0m
chaiml-bol-v5-opusdv1b-56373-v1-uploader: [38;20m2026-02-03 06:39:21 INFO base.py L1145: start to compute imatrix[0m
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Quantizing model.layers.0:   0%|          | 0/94 [00:00<?, ?it/s]/usr/local/lib/python3.12/dist-packages/torch/backends/cuda/__init__.py:131: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
chaiml-bol-v5-opusdv1b-56373-v1-uploader:   return torch._C._get_cublas_allow_tf32()
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:25.020000 7 torch/_dynamo/convert_frame.py:1358] [6/8] torch._dynamo hit config.recompile_limit (8)
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:25.020000 7 torch/_dynamo/convert_frame.py:1358] [6/8]    function: 'forward' (/usr/local/lib/python3.12/dist-packages/transformers/models/qwen3_moe/modeling_qwen3_moe.py:208)
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:25.020000 7 torch/_dynamo/convert_frame.py:1358] [6/8]    last reason: 6/7: self._modules['up_proj'].imatrix_cnt == 1358             # module.imatrix_cnt += input.shape[0]  # auto_round/compressors/base.py:1179 in get_imatrix_hook (HINT: torch.compile considers integer attributes of the nn.Module to be static. If you are observing recompilation, you might want to make this integer dynamic using torch._dynamo.config.allow_unspec_int_on_nn_module = True, or convert this integer into a tensor.)
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:25.020000 7 torch/_dynamo/convert_frame.py:1358] [6/8] To log all recompilation reasons, use TORCH_LOGS="recompiles".
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:25.020000 7 torch/_dynamo/convert_frame.py:1358] [6/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:27.900000 7 torch/_dynamo/convert_frame.py:1358] [3/8] torch._dynamo hit config.recompile_limit (8)
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:27.900000 7 torch/_dynamo/convert_frame.py:1358] [3/8]    function: 'forward' (/usr/local/lib/python3.12/dist-packages/transformers/models/qwen3_moe/modeling_qwen3_moe.py:305)
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:27.900000 7 torch/_dynamo/convert_frame.py:1358] [3/8]    last reason: 3/7: self._modules['self_attn']._modules['k_proj'].imatrix_cnt == 56  # module.imatrix_cnt += input.shape[0]  # auto_round/compressors/base.py:1179 in get_imatrix_hook (HINT: torch.compile considers integer attributes of the nn.Module to be static. If you are observing recompilation, you might want to make this integer dynamic using torch._dynamo.config.allow_unspec_int_on_nn_module = True, or convert this integer into a tensor.)
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:27.900000 7 torch/_dynamo/convert_frame.py:1358] [3/8] To log all recompilation reasons, use TORCH_LOGS="recompiles".
chaiml-bol-v5-opusdv1b-56373-v1-uploader: W0203 06:40:27.900000 7 torch/_dynamo/convert_frame.py:1358] [3/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html
chaiml-bol-v5-opusdv1b-56373-v1-uploader: [33;1m2026-02-03 06:40:45 WARNING gguf.py L297: please use more data via setting `nsamples` to improve accuracy as calibration activations contain 0[0m
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Failed to get response for submission chaiml-csfs-v3-3-dpo-lr_86358_v2: ('http://guanaco-model-mesh-load-balancer.model-mesh.k2.chaiverse.com/models/chaiml-csfs-v3-3-dpo-lr_86358_v2/predict', '{"detail":"1 validation error for RuntimeResponse\\npredictions\\n  Field required [type=missing, input_value={\'detail\': \\"503, message=...o-lr_86358_v2/predict\'\\"}, input_type=dict]\\n    For further information visit https://errors.pydantic.dev/2.12/v/missing"}')
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: 
Quantizing model.layers.0:   1%|          | 1/94 [01:37<2:31:14, 97.57s/it]
Quantizing model.layers.1:   1%|          | 1/94 [01:37<2:31:14, 97.57s/it]
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Quantizing model.layers.26:  29%|██▊       | 27/94 [21:42<49:25, 44.26s/it]
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Quantizing model.layers.32:  35%|███▌      | 33/94 [26:08<45:07, 44.38s/it]
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Quantizing model.layers.33:  36%|███▌      | 34/94 [26:52<44:19, 44.32s/it]
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Quantizing model.layers.34:  37%|███▋      | 35/94 [27:37<43:36, 44.35s/it]
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Quantizing model.layers.35:  38%|███▊      | 36/94 [28:21<42:52, 44.35s/it]
Quantizing model.layers.36:  38%|███▊      | 36/94 [28:21<42:52, 44.35s/it]
Quantizing model.layers.36:  39%|███▉      | 37/94 [29:07<42:40, 44.91s/it]
Quantizing model.layers.37:  39%|███▉      | 37/94 [29:07<42:40, 44.91s/it]
Quantizing model.layers.37:  40%|████      | 38/94 [29:52<41:47, 44.78s/it]
Quantizing model.layers.38:  40%|████      | 38/94 [29:52<41:47, 44.78s/it]
Quantizing model.layers.38:  41%|████▏     | 39/94 [30:36<40:56, 44.67s/it]
Quantizing model.layers.39:  41%|████▏     | 39/94 [30:36<40:56, 44.67s/it]
Quantizing model.layers.39:  43%|████▎     | 40/94 [31:20<39:55, 44.36s/it]
Quantizing model.layers.40:  43%|████▎     | 40/94 [31:20<39:55, 44.36s/it]
Quantizing model.layers.40:  44%|████▎     | 41/94 [32:04<39:06, 44.28s/it]
Quantizing model.layers.41:  44%|████▎     | 41/94 [32:04<39:06, 44.28s/it]
Quantizing model.layers.41:  45%|████▍     | 42/94 [32:48<38:22, 44.28s/it]
Quantizing model.layers.42:  45%|████▍     | 42/94 [32:48<38:22, 44.28s/it]
Quantizing model.layers.42:  46%|████▌     | 43/94 [33:32<37:31, 44.16s/it]
Quantizing model.layers.43:  46%|████▌     | 43/94 [33:32<37:31, 44.16s/it]
Quantizing model.layers.43:  47%|████▋     | 44/94 [34:16<36:49, 44.19s/it]
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Quantizing model.layers.44:  48%|████▊     | 45/94 [35:01<36:08, 44.26s/it]
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Quantizing model.layers.46:  50%|█████     | 47/94 [36:29<34:41, 44.29s/it]
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Quantizing model.layers.47:  51%|█████     | 48/94 [37:14<33:58, 44.32s/it]
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Quantizing model.layers.48:  52%|█████▏    | 49/94 [37:58<33:13, 44.31s/it]
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Quantizing model.layers.49:  53%|█████▎    | 50/94 [38:42<32:27, 44.26s/it]
Quantizing model.layers.50:  53%|█████▎    | 50/94 [38:42<32:27, 44.26s/it]
Quantizing model.layers.50:  54%|█████▍    | 51/94 [39:27<31:45, 44.32s/it]
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Quantizing model.layers.51:  55%|█████▌    | 52/94 [40:11<31:02, 44.34s/it]
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Quantizing model.layers.52:  56%|█████▋    | 53/94 [40:55<30:19, 44.37s/it]
Quantizing model.layers.53:  56%|█████▋    | 53/94 [40:55<30:19, 44.37s/it]
Quantizing model.layers.53:  57%|█████▋    | 54/94 [41:40<29:34, 44.37s/it]
Quantizing model.layers.54:  57%|█████▋    | 54/94 [41:40<29:34, 44.37s/it]
Quantizing model.layers.54:  59%|█████▊    | 55/94 [42:24<28:52, 44.44s/it]
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Quantizing model.layers.55:  60%|█████▉    | 56/94 [43:09<28:16, 44.64s/it]
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Quantizing model.layers.56:  61%|██████    | 57/94 [43:54<27:28, 44.55s/it]
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Quantizing model.layers.62:  67%|██████▋   | 63/94 [48:18<22:49, 44.18s/it]
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Quantizing model.layers.66:  71%|███████▏  | 67/94 [51:15<19:55, 44.27s/it]
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Quantizing model.layers.67:  72%|███████▏  | 68/94 [51:59<19:13, 44.35s/it]
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Quantizing model.layers.68:  73%|███████▎  | 69/94 [52:43<18:27, 44.30s/it]
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Quantizing model.layers.93: 100%|██████████| 94/94 [1:11:11<00:00, 45.44s/it]
chaiml-bol-v5-opusdv1b-56373-v1-uploader: 
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packing model.layers.0.mlp.gate:   0%|          | 0/36566 [00:00<?, ?it/s]
packing model.layers.0.mlp.gate:   0%|          | 1/36566 [00:01<10:49:04,  1.07s/it]
packing model.layers.1.mlp.gate:   0%|          | 1/36566 [00:01<10:49:04,  1.07s/it]
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: Checking if ChaiML/bol-v5-opusdv1b-lr1e5ep2r64g4b01-W4A16 already exists in ChaiML
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Creating repo ChaiML/bol-v5-opusdv1b-lr1e5ep2r64g4b01-W4A16 and uploading /dev/shm/model_output to it
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: ---------- 2026-02-03 07:52:49 (0:00:00) ----------
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Files:   hashed 11/38 (26.1M/131.9G) | pre-uploaded: 0/1 (0.0/131.9G) (+27 unsure) | committed: 0/38 (0.0/131.9G) | ignored: 0
chaiml-bol-v5-opusdv1b-56373-v1-uploader: Workers: hashing: 27 | get upload mode: 0 | pre-uploading: 1 | committing: 0 | waiting: 98
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New Data Upload               : 100%|█████████▉| 3.69GB / 3.69GB, 65.7MB/s  [A
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: cp /dev/shm/model_output/model-00013-of-00027.safetensors s3://guanaco-vllm-models/chaiml-bol-v5-opusdv1b-56373-v1/model-00013-of-00027.safetensors
chaiml-bol-v5-opusdv1b-56373-v1-uploader: cp /dev/shm/model_output/model-00010-of-00027.safetensors s3://guanaco-vllm-models/chaiml-bol-v5-opusdv1b-56373-v1/model-00010-of-00027.safetensors
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chaiml-bol-v5-opusdv1b-56373-v1-uploader: cp /dev/shm/model_output/model-00025-of-00027.safetensors s3://guanaco-vllm-models/chaiml-bol-v5-opusdv1b-56373-v1/model-00025-of-00027.safetensors
Job chaiml-bol-v5-opusdv1b-56373-v1-uploader completed after 5335.05s with status: succeeded
Stopping job with name chaiml-bol-v5-opusdv1b-56373-v1-uploader
Pipeline stage VLLMUploader completed in 5336.92s
run pipeline stage %s
Running pipeline stage VLLMTemplater
Pipeline stage VLLMTemplater completed in 0.63s
run pipeline stage %s
Running pipeline stage VLLMDeployer
Creating inference service chaiml-bol-v5-opusdv1b-56373-v1
Waiting for inference service chaiml-bol-v5-opusdv1b-56373-v1 to be ready
HTTP Request: %s %s "%s %d %s"
HTTP Request: %s %s "%s %d %s"
Inference service chaiml-bol-v5-opusdv1b-56373-v1 ready after 550.3064069747925s
Pipeline stage VLLMDeployer completed in 553.91s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.2643895149230957s
Received healthy response to inference request in 2.133742094039917s
Received healthy response to inference request in 2.813333511352539s
Received healthy response to inference request in 2.1444644927978516s
Received healthy response to inference request in 1.9334113597869873s
Received healthy response to inference request in 2.207705020904541s
Received healthy response to inference request in 1.9730541706085205s
Received healthy response to inference request in 1.8913795948028564s
Received healthy response to inference request in 2.0067996978759766s
Received healthy response to inference request in 1.9331345558166504s
Received healthy response to inference request in 1.9449598789215088s
Received healthy response to inference request in 1.976438045501709s
Received healthy response to inference request in 1.935154914855957s
Received healthy response to inference request in 2.2302308082580566s
Received healthy response to inference request in 1.8913516998291016s
Received healthy response to inference request in 1.9577054977416992s
Received healthy response to inference request in 2.1433165073394775s
Received healthy response to inference request in 1.8142077922821045s
Received healthy response to inference request in 1.91752290725708s
Received healthy response to inference request in 2.1132280826568604s
Received healthy response to inference request in 2.220130681991577s
Received healthy response to inference request in 1.8337063789367676s
Received healthy response to inference request in 1.8773584365844727s
Received healthy response to inference request in 1.864793300628662s
Received healthy response to inference request in 2.2058773040771484s
Received healthy response to inference request in 1.848475694656372s
Received healthy response to inference request in 1.9371514320373535s
Received healthy response to inference request in 1.9637665748596191s
Received healthy response to inference request in 2.160230875015259s
Received healthy response to inference request in 2.547574281692505s
30 requests
0 failed requests
5th percentile: 1.8403525710105897
10th percentile: 1.8631615400314332
20th percentile: 1.8913740158081054
30th percentile: 1.9333283185958863
40th percentile: 1.9418365001678466
50th percentile: 1.9684103727340698
60th percentile: 2.04937105178833
70th percentile: 2.1436609029769897
80th percentile: 2.2062428474426268
90th percentile: 2.233646678924561
95th percentile: 2.42014113664627
99th percentile: 2.736263334751129
mean time: 2.056153170267741
Pipeline stage StressChecker completed in 86.40s
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 2.32s
Shutdown handler de-registered
chaiml-bol-v5-opusdv1b-_56373_v1 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 3060.85s
Shutdown handler de-registered
chaiml-bol-v5-opusdv1b-_56373_v1 status is now inactive due to auto deactivation removed underperforming models
chaiml-bol-v5-opusdv1b-_56373_v1 status is now torndown due to DeploymentManager action