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@@ -45,15 +45,17 @@ Some these benchmarks are rather slow or take a long time to run on the referenc
 # MLPerf Training v4.1 (Submission Deadline Oct 11, 2024)
 *Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.
 
-| model | reference implementation | framework | dataset
-| ---- | ---- | ---- | ---- |
-| RetinaNet | [vision/object detection](https://github.com/mlcommons/training/tree/master/single_stage_detector) | pytorch | OpenImages
-| Stable Diffusionv2 | [image generation](https://github.com/mlcommons/training/tree/master/stable_diffusion) | pytorch | LAION-400M-filtered
-| BERT-large | [language/nlp](https://github.com/mlcommons/training/tree/master/language_model/tensorflow/bert) | tensorflow | Wikipedia 2020/01/01
-| GPT3 | [language/llm](https://github.com/mlcommons/training/tree/master/large_language_model) | paxml,megatron-lm | C4
-| LLama2 70B-LoRA | [language/LLM fine-tuning](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport
-| DLRMv2 | [recommendation](https://github.com/mlcommons/training/tree/master/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot
-| RGAT | [GNN](https://github.com/mlcommons/training/tree/master/graph_neural_network) | pytorch | IGBFull
+| model | reference implementation | framework | dataset | model parameter count
+| ---- | ---- | ---- | ---- | ----
+| RetinaNet | [vision/object detection](https://github.com/mlcommons/training/tree/master/single_stage_detector) | pytorch | OpenImages |
+| Stable Diffusionv2 | [image generation](https://github.com/mlcommons/training/tree/master/stable_diffusion) | pytorch | LAION-400M-filtered |
+| BERT-large | [language/nlp](https://github.com/mlcommons/training/tree/master/language_model/tensorflow/bert) | tensorflow | Wikipedia 2020/01/01 | 340M
+| GPT3 | [language/llm](https://github.com/mlcommons/training/tree/master/large_language_model) | paxml,megatron-lm | C4 | 175B
+| LLama2 70B-LoRA | [language/LLM fine-tuning](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
+| DLRMv2 | [recommendation](https://github.com/mlcommons/training/tree/master/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot |
+| RGAT | [GNN](https://github.com/mlcommons/training/tree/master/graph_neural_network) | pytorch | IGBFull | 25M 
+
+*Note model parameter count is not the same as active parameter that are being trained in the benchmark. 
 
 # MLPerf Training v4.0 (Submission Deadline May 10, 2024)
 *Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.