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@@ -5,7 +5,7 @@ license: mit
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  ### Model description
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  Most existing mthods focused on distilling DeepSeek-R1 to improve reasoning ability. However, as far as we know, there is no distilled model could surpass DeepSeek-R1 or QwQ-32B. We introduce NTele-R1-32B-DS , a state-of-the-art mathematical reasoning model that outperforms QwQ-32B across common reasoning benchmarks, including AIME2024/2025, MATH500 and GPQA-Diamond.
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- Notebly, NTele-R1-32B-DS is the first that achieves **more than 80/70 in challenging AIME2024/2025**.
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  | Model | Trained From | Release Date | AIME2024(ours/reported) | AIME2025(o/r) | MATH500(o/r) | GPQA-Diamond(o/r) |
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  |-------|-------|-------|-------|-------|-------|-------|
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  | QwQ-32B | - | 25.3.6 | 76.25 / 79.5 | 67.30 / - | 94.6 / - | 63.6 / - |
 
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  ### Model description
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  Most existing mthods focused on distilling DeepSeek-R1 to improve reasoning ability. However, as far as we know, there is no distilled model could surpass DeepSeek-R1 or QwQ-32B. We introduce NTele-R1-32B-DS , a state-of-the-art mathematical reasoning model that outperforms QwQ-32B across common reasoning benchmarks, including AIME2024/2025, MATH500 and GPQA-Diamond.
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+ Notely, NTele-R1-32B-DS is the first that achieves **more than 80/70 in challenging AIME2024/2025**.
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  | Model | Trained From | Release Date | AIME2024(ours/reported) | AIME2025(o/r) | MATH500(o/r) | GPQA-Diamond(o/r) |
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  |-------|-------|-------|-------|-------|-------|-------|
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  | QwQ-32B | - | 25.3.6 | 76.25 / 79.5 | 67.30 / - | 94.6 / - | 63.6 / - |