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[GH-ISSUE #1666] KTransformers+SGLang Inference Deployment fail #1072
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kvcache-ai/ktransformers#1072
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Originally created by @Yunboxun on GitHub (Dec 4, 2025).
Original GitHub issue: https://github.com/kvcache-ai/ktransformers/issues/1666
Originally assigned to: @SkqLiao on GitHub.
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System Info
CPU信息 (CPU Info)
架构:x86_64 (64-bit, Little Endian)
型号:Intel(R) Xeon(R) Gold 5418Y
核心配置:
物理CPU数量:2颗
每颗核心数:24核
每核线程数:2线程
总逻辑CPU数:96核
AVX-512、AMX-BF16、AMX-TILE、AMX-INT8 指令集支持
cpu内存:960G
GPU信息
GPU型号:8 × NVIDIA L20
驱动版本:570.124.06
CUDA版本:12.9
单卡规格:
显存:46,068 MiB (约45GB)
Reproduction
运行指令,是我哪里配置不对吗,--kt-threadpool-count从2-50我都试过
python3 -m sglang.launch_server --host 0.0.0.0 --port 8080 --model /hbox2dir/Kimi-K2-Thinking --kt-weight-path /hbox2dir/Kimi-K2-Thinking-CPU-weight --kt-cpuinfer 88 --kt-threadpool-count 2 --kt-num-gpu-experts 1 --kt-method AMXINT4 --attention-backend flashinfer --trust-remote-code --mem-fraction-static 0.98 --chunked-prefill-size 2048 --max-running-requests 8 --max-total-tokens 12800 --enable-mixed-chunk --tensor-parallel-size 8 --enable-p2p-check --disable-shared-experts-fusionOthers
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@SkqLiao commented on GitHub (Dec 5, 2025):
Oh, it seems to be an issue with SGLang...
Anyway, we will be releasing a new version that support native Kimi-K2INT4 support with GPU layerwise prefill, so stay tuned.
@ErvinXie commented on GitHub (Dec 8, 2025):
We have already release the new version, please try new v0.4.3.