diff --git a/mlperf_logging/compliance_checker/training_6.0.0/closed_common.yaml b/mlperf_logging/compliance_checker/training_6.0.0/closed_common.yaml
index c17d1432..7b5c4b12 100755
--- a/mlperf_logging/compliance_checker/training_6.0.0/closed_common.yaml
+++ b/mlperf_logging/compliance_checker/training_6.0.0/closed_common.yaml
@@ -2,7 +2,7 @@
 - KEY:
     NAME:  submission_benchmark
     REQ:   EXACTLY_ONE
-    CHECK: " v['value'] in ['flux1', 'dlrm_dcnv2', 'llama31_8b', 'llama2_70b_lora', 'llama31_405b'] "
+    CHECK: " v['value'] in ['flux1', 'dlrm_dcnv2', 'llama31_8b', 'llama2_70b_lora', 'llama31_405b', 'deepseek_v3_671b'] "
     POST:  " enqueue_config('training_6.0.0/closed_{}.yaml'.format(v['value'])) "
 
 - KEY:
diff --git a/mlperf_logging/compliance_checker/training_6.0.0/closed_deepseek_v3_671b.yaml b/mlperf_logging/compliance_checker/training_6.0.0/closed_deepseek_v3_671b.yaml
new file mode 100644
index 00000000..07059d7e
--- /dev/null
+++ b/mlperf_logging/compliance_checker/training_6.0.0/closed_deepseek_v3_671b.yaml
@@ -0,0 +1,74 @@
+- KEY:
+    NAME:  global_batch_size
+    REQ:   EXACTLY_ONE
+    POST: >
+        s['global_batch_size'] = v['value']
+
+- KEY:
+    NAME:  max_sequence_length
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 4096 "
+
+- KEY:
+    NAME:  opt_name
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 'adamw' "
+
+- KEY:
+    NAME:  opt_base_learning_rate
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_learning_rate_warmup_steps
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_learning_rate_decay_steps
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_learning_rate_decay_schedule
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 'cosine with linear warmup' "
+
+- KEY:
+    NAME:  opt_adamw_beta_1
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 0.9 "
+
+- KEY:
+    NAME:  opt_adamw_beta_2
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 0.95 "
+
+- KEY:
+    NAME:  opt_adamw_epsilon
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 1e-08 "
+
+- KEY:
+    NAME:  opt_adamw_weight_decay
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 0.1 "
+
+- KEY:
+    NAME:  opt_gradient_clip_norm
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 1.0 "
+
+- KEY:
+    NAME:  gradient_accumulation_steps
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] > 0 "
+
+- KEY:
+    NAME:  eval_samples
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 1024 "
+
+- KEY:
+    NAME:  eval_accuracy
+    REQ:   AT_LEAST_ONE
+    CHECK:
+        - "'samples_count' in v['metadata']"
+    ATLEAST_ONE_CHECK: "(v['value'] <= 2.7) and v['value'] > 0.0"  # TODO(dfridman): Update this once we have the exact value
diff --git a/mlperf_logging/compliance_checker/training_6.0.0/open_common.yaml b/mlperf_logging/compliance_checker/training_6.0.0/open_common.yaml
index ab82d076..8b0b43a6 100644
--- a/mlperf_logging/compliance_checker/training_6.0.0/open_common.yaml
+++ b/mlperf_logging/compliance_checker/training_6.0.0/open_common.yaml
@@ -2,5 +2,5 @@
 - KEY:
     NAME:  submission_benchmark
     REQ:   EXACTLY_ONE
-    CHECK: " v['value'] in ['flux1', 'dlrm_dcnv2', 'llama31_8b', 'llama2_70b_lora', 'llama31_405b'] "
+    CHECK: " v['value'] in ['flux1', 'dlrm_dcnv2', 'llama31_8b', 'llama2_70b_lora', 'llama31_405b', 'deepseek_v3_671b'] "
     POST:  " enqueue_config('training_6.0.0/open_{}.yaml'.format(v['value'])) "
diff --git a/mlperf_logging/compliance_checker/training_6.0.0/open_deepseek_v3_671b.yaml b/mlperf_logging/compliance_checker/training_6.0.0/open_deepseek_v3_671b.yaml
new file mode 100644
index 00000000..a9f73830
--- /dev/null
+++ b/mlperf_logging/compliance_checker/training_6.0.0/open_deepseek_v3_671b.yaml
@@ -0,0 +1,65 @@
+- KEY:
+    NAME:  global_batch_size
+    REQ:   EXACTLY_ONE
+    POST: >
+        s['global_batch_size'] = v['value']
+
+- KEY:
+    NAME:  max_sequence_length
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 4096 "
+
+- KEY:
+    NAME:  opt_name
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 'adamw' "
+
+- KEY:
+    NAME:  opt_base_learning_rate
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_learning_rate_warmup_steps
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_learning_rate_decay_schedule
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_adamw_beta_1
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_adamw_beta_2
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_adamw_epsilon
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_adamw_weight_decay
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  opt_gradient_clip_norm
+    REQ:   EXACTLY_ONE
+
+- KEY:
+    NAME:  gradient_accumulation_steps
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] > 0 "
+
+- KEY:
+    NAME:  eval_samples
+    REQ:   EXACTLY_ONE
+    CHECK: " v['value'] == 1024 "
+
+- KEY:
+    NAME:  eval_accuracy
+    REQ:   AT_LEAST_ONE
+    CHECK:
+        - "'epoch_num' in v['metadata']"
+    ATLEAST_ONE_CHECK: "(v['value'] <= 2.7) and v['value'] > 0.0"  # TODO(dfridman): Update this once we have the exact value
+
diff --git a/mlperf_logging/mllog/constants.py b/mlperf_logging/mllog/constants.py
index 57972a6f..3016f0a3 100644
--- a/mlperf_logging/mllog/constants.py
+++ b/mlperf_logging/mllog/constants.py
@@ -57,6 +57,7 @@
 LLAMA31_405B = "llama31_405b"
 LLAMA31_8B = "llama31_8b"
 FLUX1 = "flux1"
+DEEPSEEK_V3_671B = "deepseek_v3_671b"
 
 # Constant values - model info
 ADAGRAD = "adagrad"