Next up, let’s load the model onto our GPUs. It’s time to understand what we’re working with and make hardware decisions. Kimi-K2-Thinking is a state-of-the-art open weight model. It’s a 1 trillion parameter mixture-of-experts model with multi-headed latent attention, and the (non-shared) expert weights are quantized to 4 bits. This means it comes out to 594 GB with 570 GB of that for the quantized experts and 24 GB for everything else.
对比Sora 2和Veo 3.1两大竞品，Seedance 2.0在多个维度上展现出差异化优势，同时也暴露出一些劣势。。新收录的资料对此有专业解读
github.com/swc-17/Spar… github.com/swc-17/Spar…，推荐阅读新收录的资料获取更多信息
同时，庞大的订单规模（全年现制饮品销量达41亿杯，同比增长39%）推动供应链议价能力提升，叠加数字化运营对人力、库存成本的优化，即便面临行业竞争压力，全年GAAP营业利润仍达50.73亿元，营业利润率维持在10.3%。。新收录的资料是该领域的重要参考