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6e3b674
Rename benchmark directories to model names
ShriyaRishab Oct 7, 2026
64f43a0
Simplify benchmark model tables
ShriyaRishab Oct 7, 2026
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12 changes: 6 additions & 6 deletions .gitmodules
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Original file line number Diff line number Diff line change
@@ -1,12 +1,12 @@
[submodule "recommendation/dlrm"]
path = retired_benchmarks/dlrm/dlrm
[submodule "dlrm_dcnv2/dlrm"]
path = retired_benchmarks/dlrm_dcnv2/dlrm
url = https://github.com/facebookresearch/dlrm.git
branch = mlperf
[submodule "flux/torchtitan"]
path = text_to_image/torchtitan
[submodule "flux1/torchtitan"]
path = flux1/torchtitan
url = https://github.com/pytorch/torchtitan.git
branch = mlperf-training-flux.1
[submodule "llm_post_training/RL"]
path = llm_post_training/RL
[submodule "qwen35_397b_grpo/RL"]
path = qwen35_397b_grpo/RL
url = https://github.com/NVIDIA-NeMo/RL.git
branch = mlperf-training-qwen35-main
114 changes: 56 additions & 58 deletions README.md
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Expand Up @@ -44,47 +44,47 @@ Some these benchmarks are rather slow or take a long time to run on the referenc

# MLPerf Training v6.1 (Submission Deadline Oct 16, 2026)

| Model | reference implementation | framework* | dataset | model parameter count**
| ---- | ---- | ---- | ---- | ----
| flux.1 | [text_to_image](https://github.com/mlcommons/training/tree/master/text_to_image) | torchtitan | CC12M subset | 11.9B
| llama3.1_8b | [small_llm_pretraining](https://github.com/mlcommons/training/tree/master/small_llm_pretraining) | NeMo | C4 | 8b
| llama2_70b_lora | [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| gpt_oss_20b | [small_llm_moe_pretraining](https://github.com/mlcommons/training/tree/master/small_llm_moe_pretraining/primus) | Primus | C4 | 20B |
| deepseekv3 | [llm_moe_pretraining](https://github.com/mlcommons/training/tree/master/llm_moe_pretraining/nemo) | NeMo | C4 | 671B |
| qwen35_397b_grpo | [llm_post_training](https://github.com/mlcommons/training/tree/master/llm_post_training) | NeMo-RL / NeMo-Gym | SWE tasks | 397B
| dlrm_v4_hstu | [recommendation](https://github.com/mlcommons/training/tree/master/recommendation) | pytorch | Yambda-5b | HSTU
| model | framework* | dataset | model parameter count**
| ---- | ---- | ---- | ----
| [flux1](https://github.com/mlcommons/training/tree/master/flux1) | torchtitan | CC12M subset | 11.9B
| [llama31_8b](https://github.com/mlcommons/training/tree/master/llama31_8b) | NeMo | C4 | 8b
| [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| [gpt_oss_20b](https://github.com/mlcommons/training/tree/master/gpt_oss_20b/primus) | Primus | C4 | 20B |
| [deepseekv3_671b](https://github.com/mlcommons/training/tree/master/deepseekv3_671b/nemo) | NeMo | C4 | 671B |
| [qwen35_397b_grpo](https://github.com/mlcommons/training/tree/master/qwen35_397b_grpo) | NeMo-RL / NeMo-Gym | SWE tasks | 397B
| [dlrmv4](https://github.com/mlcommons/training/tree/master/dlrmv4) | pytorch | Yambda-5b | HSTU

*Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.

**Model parameter count is not the same as active parameter that are being trained in the benchmark.

# MLPerf Training v6.0 (Submission Deadline May 15, 2026)

| Model | reference implementation | framework* | dataset | model parameter count**
| ---- | ---- | ---- | ---- | ----
| flux.1 | [text_to_image](https://github.com/mlcommons/training/tree/master/text_to_image) | torchtitan | CC12M subset | 11.9B
| llama3.1_8b | [small_llm_pretraining](https://github.com/mlcommons/training/tree/master/small_llm_pretraining) | NeMo | C4 | 8b
| llama2_70b_lora | [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| llama3.1_405b | [large_language_model_pretraining](https://github.com/mlcommons/training/tree/master/retired_benchmarks/large_language_model_pretraining) | NeMo | C4 | 405B
| dlrm_dcnv2 | [recommendation_v2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| gpt_oss_20b | [small_llm_moe_pretraining](https://github.com/mlcommons/training/tree/master/small_llm_moe_pretraining/primus) | Primus | C4 | 20B |
| deepseekv3 | [llm_moe_pretraining](https://github.com/mlcommons/training/tree/master/llm_moe_pretraining/nemo) | NeMo | C4 | 671B |
| model | framework* | dataset | model parameter count**
| ---- | ---- | ---- | ----
| [flux1](https://github.com/mlcommons/training/tree/master/flux1) | torchtitan | CC12M subset | 11.9B
| [llama31_8b](https://github.com/mlcommons/training/tree/master/llama31_8b) | NeMo | C4 | 8b
| [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| [llama31_405b](https://github.com/mlcommons/training/tree/master/retired_benchmarks/llama31_405b) | NeMo | C4 | 405B
| [dlrm_dcnv2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/dlrm_dcnv2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| [gpt_oss_20b](https://github.com/mlcommons/training/tree/master/gpt_oss_20b/primus) | Primus | C4 | 20B |
| [deepseekv3_671b](https://github.com/mlcommons/training/tree/master/deepseekv3_671b/nemo) | NeMo | C4 | 671B |

*Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.

**Model parameter count is not the same as active parameter that are being trained in the benchmark.

# MLPerf Training v5.1 (Submission Deadline Oct 10, 2025)

| Model | reference implementation | framework* | dataset | model parameter count**
| ---- | ---- | ---- | ---- | ----
| retinanet | [single_stage_detector](https://github.com/mlcommons/training/tree/master/single_stage_detector) | pytorch | OpenImages | 37M
| flux.1 | [text_to_image](https://github.com/mlcommons/training/tree/master/text_to_image) | torchtitan | CC12M subset | 11.9B
| llama3.1_8b | [small_llm_pretraining](https://github.com/mlcommons/training/tree/master/small_llm_pretraining) | NeMo | C4 | 8b
| llama2_70b_lora | [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| llama3.1_405b | [large_language_model_pretraining](https://github.com/mlcommons/training/tree/master/retired_benchmarks/large_language_model_pretraining) | NeMo | C4 | 405B
| dlrm_dcnv2 | [recommendation_v2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| rgat | [graph_neural_network](https://github.com/mlcommons/training/tree/master/graph_neural_network) | GLT | IGBH-Full | 25M
| model | framework* | dataset | model parameter count**
| ---- | ---- | ---- | ----
| [retinanet](https://github.com/mlcommons/training/tree/master/retired_benchmarks/retinanet) | pytorch | OpenImages | 37M
| [flux1](https://github.com/mlcommons/training/tree/master/flux1) | torchtitan | CC12M subset | 11.9B
| [llama31_8b](https://github.com/mlcommons/training/tree/master/llama31_8b) | NeMo | C4 | 8b
| [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| [llama31_405b](https://github.com/mlcommons/training/tree/master/retired_benchmarks/llama31_405b) | NeMo | C4 | 405B
| [dlrm_dcnv2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/dlrm_dcnv2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| [rgat](https://github.com/mlcommons/training/tree/master/retired_benchmarks/rgat) | GLT | IGBH-Full | 25M

*Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.

Expand All @@ -95,44 +95,42 @@ Some these benchmarks are rather slow or take a long time to run on the referenc
* Framework here is given for the reference implementation. Submitters are free to use their own frameworks to run the benchmark.
* Model parameter count is not the same as active parameter that are being trained in the benchmark.

| Model | reference implementation | framework | dataset | model parameter count
| ---- | ---- | ---- | ---- | ----
| retinanet | [single_stage_detector](https://github.com/mlcommons/training/tree/master/single_stage_detector) | pytorch | OpenImages | 37M
| Stable Diffusionv2 | [image generation](https://github.com/mlcommons/training/tree/master/stable_diffusion) | pytorch | LAION-400M-filtered | 865M
| bert | [language_model](https://github.com/mlcommons/training/tree/master/language_model/tensorflow/bert) | tensorflow | Wikipedia 2020/01/01 | 340M
| llama3.1_405b | [large_language_model_pretraining](https://github.com/mlcommons/training/tree/master/retired_benchmarks/large_language_model_pretraining) | NeMo | C4 | 405B
| llama2_70b_lora | [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| dlrm_dcnv2 | [recommendation_v2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| rgat | [graph_neural_network](https://github.com/mlcommons/training/tree/master/graph_neural_network) | GLT | IGBH-Full | 25M
| model | framework | dataset | model parameter count
| ---- | ---- | ---- | ----
| [retinanet](https://github.com/mlcommons/training/tree/master/retired_benchmarks/retinanet) | pytorch | OpenImages | 37M
| [stable_diffusion](https://github.com/mlcommons/training/tree/master/retired_benchmarks/stable_diffusion) | pytorch | LAION-400M-filtered | 865M
| [bert](https://github.com/mlcommons/training/tree/master/retired_benchmarks/bert) | tensorflow | Wikipedia 2020/01/01 | 340M
| [llama31_405b](https://github.com/mlcommons/training/tree/master/retired_benchmarks/llama31_405b) | NeMo | C4 | 405B
| [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| [dlrm_dcnv2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/dlrm_dcnv2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| [rgat](https://github.com/mlcommons/training/tree/master/retired_benchmarks/rgat) | GLT | IGBH-Full | 25M

# 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 | model parameter count
| ---- | ---- | ---- | ---- | ----
| RetinaNet | [vision/object detection](https://github.com/mlcommons/training/tree/master/single_stage_detector) | pytorch | OpenImages | 37M
| Stable Diffusionv2 | [image generation](https://github.com/mlcommons/training/tree/master/stable_diffusion) | pytorch | LAION-400M-filtered | 865M
| 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/retired_benchmarks/recommendation_v2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| RGAT | [GNN](https://github.com/mlcommons/training/tree/master/graph_neural_network) | pytorch | IGBH-Full | 25M
| model | framework | dataset | model parameter count
| ---- | ---- | ---- | ----
| [retinanet](https://github.com/mlcommons/training/tree/master/retired_benchmarks/retinanet) | pytorch | OpenImages | 37M
| [stable_diffusion](https://github.com/mlcommons/training/tree/master/retired_benchmarks/stable_diffusion) | pytorch | LAION-400M-filtered | 865M
| [bert](https://github.com/mlcommons/training/tree/master/retired_benchmarks/bert) | tensorflow | Wikipedia 2020/01/01 | 340M
| [gpt3](https://github.com/mlcommons/training/tree/master/retired_benchmarks/gpt3) | paxml,megatron-lm | C4 | 175B
| [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport | 70B
| [dlrm_dcnv2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/dlrm_dcnv2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot | 167M
| [rgat](https://github.com/mlcommons/training/tree/master/retired_benchmarks/rgat) | pytorch | IGBH-Full | 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.

| model | reference implementation | framework | dataset
| ---- | ---- | ---- | ---- |
| resnet50v1.5 | [vision/classification_and_detection](https://github.com/mlcommons/training/tree/master/image_classification) | tensorflow2 | Imagenet
| RetinaNet | [vision/object detection](https://github.com/mlcommons/training/tree/master/single_stage_detector) | pytorch | OpenImages
| 3DUnet | [vision/image segmentation](https://github.com/mlcommons/training/tree/master/image_segmentation/pytorch) | pytorch | KiTS19
| 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/retired_benchmarks/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 | framework | dataset
| ---- | ---- | ---- |
| [resnet](https://github.com/mlcommons/training/tree/master/retired_benchmarks/resnet) | tensorflow2 | Imagenet
| [retinanet](https://github.com/mlcommons/training/tree/master/retired_benchmarks/retinanet) | pytorch | OpenImages
| [unet3d](https://github.com/mlcommons/training/tree/master/retired_benchmarks/unet3d/pytorch) | pytorch | KiTS19
| [stable_diffusion](https://github.com/mlcommons/training/tree/master/retired_benchmarks/stable_diffusion) | pytorch | LAION-400M-filtered
| [bert](https://github.com/mlcommons/training/tree/master/retired_benchmarks/bert) | tensorflow | Wikipedia 2020/01/01
| [gpt3](https://github.com/mlcommons/training/tree/master/retired_benchmarks/gpt3) | paxml,megatron-lm | C4
| [llama2_70b_lora](https://github.com/mlcommons/training/tree/master/llama2_70b_lora) | pytorch | SCROLLS GovReport
| [dlrm_dcnv2](https://github.com/mlcommons/training/tree/master/retired_benchmarks/dlrm_dcnv2/torchrec_dlrm) | torchrec | Criteo 3.5TB multi-hot
| [rgat](https://github.com/mlcommons/training/tree/master/retired_benchmarks/rgat) | pytorch | IGBFull
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