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## Model Overview
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We release PCL-Reasoner-V1, a model trained based on Qwen2.5-32B-Base and undergoes high-performance supervised fine-tuning based on the MindSpore framework and Ascend hardware. After fine-tuning, the model demonstrates significant improvements in mathematical reasoning capabilities. PCL-Reasoner-V1 achieves 85.7% and 84.2% respectively on AIME 24 and AIME 25, which position PCL-Reasoner-V1 among the top-tier models in the 32B parameter class on AIME24/25.
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We have fully open-sourced the model weights, dataset and training code. Follow the tutorial below to deploy and explore post-training!
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## Code
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https://github.com/PCL-Reasoner/V1
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## Model Overview
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We release PCL-Reasoner-V1, a model trained based on Qwen2.5-32B-Base and undergoes high-performance supervised fine-tuning based on the MindSpore framework and Ascend hardware. After fine-tuning, the model demonstrates significant improvements in mathematical reasoning capabilities. PCL-Reasoner-V1 achieves 85.7% and 84.2% respectively on AIME 24 and AIME 25, which position PCL-Reasoner-V1 among the top-tier models in the 32B parameter class on AIME24/25.
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We have fully open-sourced the model weights, dataset and training code. Follow the tutorial below to deploy and explore post-training!
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## Code
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https://github.com/PCL-Reasoner/V1
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