warmup16 {"status": 200, "elapsed_s": 2.567105770111084, "ttft_s": null, "chunks": 18, "content_chunks": 16, "post_first_tok_s_estimate": 6.232699948046023, "text": "彩虹之所以有多种颜色，是因为阳光（白光）被空气中的水滴折射、反射", "chars": 32}
decode64 {"status": 200, "elapsed_s": 9.786075592041016, "ttft_s": null, "chunks": 66, "content_chunks": 64, "post_first_tok_s_estimate": 6.539904520260501, "text": "In mixture-of experts (MoE) inference, the model's efficiency hinges on routing each input token to only a subset of expert sub-networks. However, this sparse activation creates a critical bottleneck: **GPU communication overhead**. Unlike dense models where all parameters reside on every GPU, MoE often shards experts across multiple", "chars": 335}
math {"status": 200, "elapsed_s": 0.5457637310028076, "ttft_s": null, "chunks": 3, "content_chunks": 1, "post_first_tok_s_estimate": 29.31671544131556, "text": "410", "chars": 3}
