字节跳动Seed最新强化学习配方POLARIS开源 4B 模型数学推理接近 235B 表现
近日，字节跳动Seed团队携手香港大学与复旦大学，共同推出了创新的强化学习训练方法——POLARIS。该方法通过精心设计的Scaling RL策略，成功将小模型的数学推理能力提升至与超大模型相媲美的水平，为人工智能领域的小模型优化提供了新路径。
实验结果显示，采用POLARIS训练的40亿参数开源模型Qwen3-4B，在AIME25和AIME24数学测试中分别取得了79.4%和81.2%的高准确率，性能超越部分更大规模的闭源模型。尤为突出的是，POLARIS-4B模型的轻量化设计，使其能够在消费级显卡上轻松部署，大大降低了应用门槛。
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