Update README.md

README.md

@@ -62,7 +62,7 @@ model-index:
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 ## Model Description
-The RLinf-math series is trained on DeepSeek-R1-Distill-Qwen (1.5B and 7B variants), using the same base models and training datasets as AReaL. Training with RLinf yields performance better than AReaL.
+The RLinf-math series is trained on DeepSeek-R1-Distill-Qwen (1.5B and 7B variants), using the same base models and training datasets as AReaL. Training with RLinf yields SOTA performance.
 
 We adopt Group Relative Policy Optimization (GRPO) with token-level loss aggregation, focusing on mathematical reasoning and long chain-of-thought (CoT) tasks.
 
@@ -77,23 +77,33 @@ We trained and evaluated two models using RLinf:
 
 ### Benchmark Results
 
-|                                          | AIME24 | AIME25 | GPQA-diamond |
-| ---------------------------------------- | ------ | ------ | ------------ |
-| [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)            | 28.33  | 24.90  | 27.45        |
-| [DeepScaleR-1.5B-Preview](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview)            | 40.41  | 30.93  | 27.54        |
-| [AReaL-1.5B](https://huggingface.co/inclusionAI/AReaL-1.5B-Preview-Stage-3)        |  40.73  | 31.56  |  28.1        |
-| AReaL-1.5B-retrain*       |  44.42  | 34.27  |  33.81       |
-| [RLinf-math-1.5B](https://huggingface.co/RLinf/RLinf-math-1.5B)                          | **48.44**  | **35.63**  | **38.46**        |
+**1.5B models**. All models except the base model are trained upon DeepSeek-R1-Distill-Qwen-1.5B using RL. 
 
-
-|                             | AIME24 | AIME25 | GPQA-diamond |
-| --------------------------- | ------ | ------ | ------------ |
-| [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) | 54.90  | 40.20  | 45.48        |
-| [AReaL-7B](https://huggingface.co/inclusionAI/AReaL-boba-RL-7B)                    | 62.82  | 47.29  | 46.54        |
-| [RLinf-math-7B](https://huggingface.co/RLinf/RLinf-math-7B)               | **68.33**  | **52.19**  | **48.18**        |
+| Model                                      | AIME 24   | AIME 25   | GPQA-diamond | Average   |
+| ------------------------------------------ | --------- | --------- | ------------ | --------- |
+| [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) | 28.33     | 24.90     | 27.45        | 26.89     |
+| [DeepMath-1.5B](https://huggingface.co/zwhe99/DeepMath-1.5B)                             | 37.80     | 30.42     | 32.11        | 33.44     |
+| [DeepScaleR-1.5B-Preview](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview)                    | 40.41     | 30.93     | 27.54        | 32.96     |
+| [AReaL-1.5B-Preview-Stage-3](https://huggingface.co/inclusionAI/AReaL-1.5B-Preview-Stage-3)                 | 40.73     | 31.56     | 28.10        | 33.46     |
+| AReaL-1.5B-retrain*                        | 44.42     | 34.27     | 33.81        | 37.50     |
+| [FastCuRL-1.5B-V3](https://huggingface.co/Nickyang/FastCuRL-1.5B-V3)                          | 43.65     | 32.49     | 35.00        | 37.05     |
+| [RLinf-math-1.5B](https://huggingface.co/RLinf/RLinf-math-1.5B)                           | **48.44** | **35.63** | **38.46**    | **40.84** |
 
 \* We retrain the model using the default settings for 600 steps. 
 
+**7B models**. All models except the base model are trained upon DeepSeek-R1-Distill-Qwen-7B using RL. 
+
+| Model                                    | AIME 24   | AIME 25   | GPQA-diamond | Average   |
+| ---------------------------------------- | --------- | --------- | ------------ | --------- |
+| [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B)  | 54.90     | 40.20     | 45.48        | 46.86     |
+| [AReaL-boba-RL-7B](https://huggingface.co/inclusionAI/AReaL-boba-RL-7B)                           | 61.66     | 49.38     | 46.93        | 52.66     |
+| [Skywork-OR1-7B](https://huggingface.co/Skywork/Skywork-OR1-7B)                           | 66.87     | 52.49     | 44.43        | 54.60     |
+| [Polaris-7B-Preview](https://huggingface.co/POLARIS-Project/Polaris-7B-Preview)                    | **68.55** | 51.24     | 43.88        | 54.56     |
+| [AceMath-RL-Nemotron-7B](https://huggingface.co/nvidia/AceMath-RL-Nemotron-7B)                   | 67.30     | **55.00** | 45.57        | 55.96     |
+| [RLinf-math-7B](https://huggingface.co/RLinf/RLinf-math-7B)                            | 68.33     | 52.19     | **48.18**    | **56.23** |
+
+
+
 ## How to Use
 Example with Hugging Face `transformers`: