Prime Intellect 用 NIXL 和 ModelExpress 将 GLM-5.2 的 RL 权重传输压缩到 4 秒
Prime Intellect 基于 NIXL 和 ModelExpress 重建权重交接流程,把 GLM-5.2 的 RL 权重传输从 60-90 秒降到个位数秒,并去掉了静态进程组限制。此前 prime-rl 在 28 个 H200 节点上训练 GLM-5 这类万亿参数模型,单步时间已低于 5 分钟,但每步训练器到推理端的权重同步始终卡在 60-90 秒。按 GLM-5.2 bf16 约 1,600GB 权重、单 GPU 400Gb/s NIC 估算,理论下限约 1.0 秒。

? We will cover our approach to this in the following sections. Weight format hell vLLM starts from checkpoint-format tensors - the names, shapes, and dtypes stored on disk or the Hugging Face Hub - and transforms them into runtime kernel format. The result depends on the model architecture, parallelism strategy, GPU, quantization mode, and selected kernels. For example, an MoE loader may pack the gate and up projections (w1 and w3) into w13 weight. Quantized kernels may additionally cast, trans
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