diff --git a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice.mdx b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice.mdx
index c8d6ae156..b39552a39 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice.mdx
@@ -636,6 +636,156 @@ you encounter issues or have any questions, please [open an issue](https://githu
+## MiniMax Series Models
+
+### Low Latency
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Model |
+ Hardware |
+ Cards |
+ Deploy Mode |
+ Dataset |
+ TPOT |
+ Quantization |
+ Configuration |
+
+
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 8 |
+ PD Mixed |
+ 3.5K+1.5K |
+ 20ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 8 |
+ PD Mixed |
+ 128K+1K |
+ 20ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+
+
+### High Throughput
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Model |
+ Hardware |
+ Cards |
+ Deploy Mode |
+ Dataset |
+ TPOT |
+ Quantization |
+ Configuration |
+
+
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 8 |
+ PD Mixed |
+ 3.5K+1.5K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 8 |
+ PD Mixed |
+ 32K+1K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 8 |
+ PD Mixed |
+ 64K+1K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 8 |
+ PD Mixed |
+ 128K+1K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 4 |
+ PD Mixed |
+ 64K+1K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 16 |
+ PD Disaggregation |
+ 64K+1K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+ | MiniMax-M2.5 |
+ Atlas 800I A3 |
+ 16 |
+ PD Disaggregation |
+ 128K+1K |
+ 50ms |
+ W8A8 INT8 |
+ Optimal Configuration |
+
+
+
+
## Optimal Configuration
### DeepSeek-R1 3_5K-1_5K 50ms on A3 32 Cards Disaggregation Mode
@@ -4852,3 +5002,776 @@ We tested it based on the `RANDOM` dataset.
```bash Command
python3 -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 6699 --random-range-ratio 1 --max-concurrency 352 --random-output-len 1500 --random-input-len 3500 --num-prompts 1408
```
+
+### MiniMax-M2.5 3_5K-1_5K Low Latency on A3 8 Cards Mixed Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 8Card
+
+DeployMode: PD Mixed
+
+Dataset: random
+
+Input Output Length: 3.5K+1.5K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+export HCCL_SOCKET_IFNAME=lo
+export GLOO_SOCKET_IFNAME=lo
+
+export HCCL_OP_EXPANSION_MODE=AIV
+export TASK_QUEUE_ENABLE=1
+
+export HCCL_BUFFSIZE=1500
+export ASCEND_USE_FIA=1
+export SGLANG_SET_CPU_AFFINITY=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_NPU_USE_MULTI_STREAM=1
+export SGLANG_NPU_FUSED_MOE_MODE=2
+export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=224000
+
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+python -m sglang.launch_server \
+ --model-path $MODEL_PATH \
+ --host 127.0.0.1 \
+ --port 32001 \
+ --tp-size 16 \
+ --dp-size 16 \
+ --enable-dp-attention \
+ --mem-fraction-static 0.75 \
+ --max-running-requests 128 \
+ --disable-radix-cache \
+ --chunked-prefill-size -1 --max-prefill-token 8192 \
+ --cuda-graph-bs 2 4 6 8 \
+ --moe-a2a-backend ascend_fuseep --deepep-mode auto --quantization modelslim \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant \
+ --dtype bfloat16 \
+ --tokenizer-worker-num 2 \
+ --prefill-delayer-max-delay-passes 500 \
+ --enable-prefill-delayer
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 32001 --random-input-len 3500 --random-output-len 1500 --num-prompts 320 --random-range-ratio 1 --max-concurrency 80
+```
+### MiniMax-M2.5 128K-1K Low Latency on A3 8 Cards Mixed Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 8Card
+
+DeployMode: PD Mixed
+
+Dataset: random
+
+Input Output Length: 128K+1K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+export HCCL_SOCKET_IFNAME=lo
+export GLOO_SOCKET_IFNAME=lo
+
+export TASK_QUEUE_ENABLE=1
+
+export ASCEND_USE_FIA=1
+export HCCL_BUFFSIZE=1600
+export SGLANG_SET_CPU_AFFINITY=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=640
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=64
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=2048
+export DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ=1
+export SGLANG_NPU_FUSED_MOE_MODE=2
+export SGLANG_NPU_DEEPEP_USE_FUSED_MOE_DECODE=1
+export SGLANG_NPU_FUSEEP_DECODE_ONLY=1
+
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+python -m sglang.launch_server \
+ --model-path $MODEL_PATH \
+ --host 127.0.0.1 \
+ --port 32000 \
+ --tp-size 16 \
+ --dp-size 2 \
+ --enable-dp-attention \
+ --prefill-delayer-max-delay-passes 100 \
+ --enable-prefill-delayer \
+ --mem-fraction-static 0.65 \
+ --max-running-requests 8 \
+ --chunked-prefill-size -1 --max-prefill-token 130000 \
+ --cuda-graph-bs 1 2 4 \
+ --moe-a2a-backend ascend_fuseep --deepep-mode auto --quantization modelslim \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant \
+ --dtype bfloat16 \
+ --trust-remote-code \
+ --tokenizer-worker-num 8
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 32000 --random-input-len 131072 --random-output-len 1024 --num-prompts 8 --random-range-ratio 1 --max-concurrency 2
+```
+### MiniMax-M2.5 3_5K-1_5K High Throughput on A3 8 Cards Mixed Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 8Card
+
+DeployMode: PD Mixed
+
+Dataset: random
+
+Input Output Length: 3.5K+1.5K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+export HCCL_SOCKET_IFNAME=lo
+export GLOO_SOCKET_IFNAME=lo
+
+export HCCL_OP_EXPANSION_MODE=AIV
+export TASK_QUEUE_ENABLE=1
+
+export HCCL_BUFFSIZE=800
+export ASCEND_USE_FIA=1
+export SGLANG_SET_CPU_AFFINITY=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_NPU_FUSED_MOE_MODE=2
+export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=204800
+
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+python -m sglang.launch_server \
+ --model-path $MODEL_PATH \
+ --host 127.0.0.1 \
+ --port 32001 \
+ --tp-size 16 \
+ --enable-dp-attention \
+ --dp-size 16 \
+ --mem-fraction-static 0.75 \
+ --max-running-requests 480 \
+ --disable-radix-cache \
+ --prefill-delayer-max-delay-passes 500 \
+ --enable-prefill-delayer \
+ --chunked-prefill-size -1 --max-prefill-token 8192 \
+ --cuda-graph-bs 8 16 24 32 48 64 80 \
+ --moe-a2a-backend ascend_fuseep --deepep-mode auto --quantization modelslim \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant \
+ --dtype bfloat16
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 32001 --random-input-len 3500 --random-output-len 1500 --num-prompts 1280 --random-range-ratio 1 --max-concurrency 320
+```
+
+### MiniMax-M2.5 64K-1K High Throughput on A3 8 Cards Mixed Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 8Card
+
+DeployMode: PD Mixed
+
+Dataset: random
+
+Input Output Length: 64K+1K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+export HCCL_SOCKET_IFNAME=lo
+export GLOO_SOCKET_IFNAME=lo
+
+export TASK_QUEUE_ENABLE=1
+
+export ASCEND_USE_FIA=1
+export HCCL_BUFFSIZE=1600
+export SGLANG_SET_CPU_AFFINITY=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=640
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=64
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=2048
+export DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ=1
+export SGLANG_NPU_FUSED_MOE_MODE=2
+export SGLANG_NPU_DEEPEP_USE_FUSED_MOE_DECODE=1
+export SGLANG_NPU_FUSEEP_DECODE_ONLY=1
+
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+python -m sglang.launch_server \
+ --model-path $MODEL_PATH \
+ --host 127.0.0.1 \
+ --port 32000 \
+ --tp-size 16 \
+ --dp-size 2 \
+ --enable-dp-attention \
+ --prefill-delayer-max-delay-passes 100 \
+ --enable-prefill-delayer \
+ --mem-fraction-static 0.65 \
+ --max-running-requests 72 \
+ --chunked-prefill-size -1 --max-prefill-token 180000 \
+ --cuda-graph-bs 8 16 24 32 40 \
+ --moe-a2a-backend ascend_fuseep --deepep-mode auto --quantization modelslim \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant \
+ --dtype bfloat16 \
+ --trust-remote-code \
+ --tokenizer-worker-num 8
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 32000 --random-input-len 65536 --random-output-len 1024 --num-prompts 144 --random-range-ratio 1 --max-concurrency 36
+```
+### MiniMax-M2.5 128K-1K High Throughput on A3 8 Cards Mixed Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 8Card
+
+DeployMode: PD Mixed
+
+Dataset: random
+
+Input Output Length: 128K+1K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+export HCCL_SOCKET_IFNAME=lo
+export GLOO_SOCKET_IFNAME=lo
+export TASK_QUEUE_ENABLE=1
+
+export ASCEND_USE_FIA=1
+export HCCL_BUFFSIZE=1600
+export SGLANG_SET_CPU_AFFINITY=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=640
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=64
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=2048
+export DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ=1
+export SGLANG_NPU_FUSED_MOE_MODE=2
+export SGLANG_NPU_DEEPEP_USE_FUSED_MOE_DECODE=1
+export SGLANG_NPU_FUSEEP_DECODE_ONLY=1
+
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+python -m sglang.launch_server \
+ --model-path $MODEL_PATH \
+ --host 127.0.0.1 \
+ --port 32000 \
+ --tp-size 16 \
+ --dp-size 2 \
+ --enable-dp-attention \
+ --prefill-delayer-max-delay-passes 100 \
+ --enable-prefill-delayer \
+ --mem-fraction-static 0.65 \
+ --max-running-requests 36 \
+ --chunked-prefill-size -1 --max-prefill-token 130000 \
+ --cuda-graph-bs 8 16 24 \
+ --moe-a2a-backend ascend_fuseep --deepep-mode auto --quantization modelslim \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant \
+ --dtype bfloat16 \
+ --trust-remote-code \
+ --tokenizer-worker-num 8
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 32000 --random-input-len 131072 --random-output-len 1024 --num-prompts 128 --random-range-ratio 1 --max-concurrency 32
+```
+### MiniMax-M2.5 64K-1K High Throughput on A3 4 Cards Mixed Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 4Card
+
+DeployMode: PD Mixed
+
+Dataset: random
+
+Input Output Length: 64K+1K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+export HCCL_SOCKET_IFNAME=lo
+export GLOO_SOCKET_IFNAME=lo
+export TASK_QUEUE_ENABLE=1
+
+export ASCEND_USE_FIA=0
+export HCCL_BUFFSIZE=1600
+export SGLANG_SET_CPU_AFFINITY=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=640
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=64
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=2048
+export DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ=1
+export SGLANG_NPU_FUSED_MOE_MODE=2
+export SGLANG_NPU_DEEPEP_USE_FUSED_MOE_DECODE=1
+export SGLANG_NPU_FUSEEP_DECODE_ONLY=1
+
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+python -m sglang.launch_server \
+ --model-path $MODEL_PATH \
+ --host 127.0.0.1 \
+ --port 32000 \
+ --tp-size 8 \
+ --enable-dp-attention \
+ --prefill-delayer-max-delay-passes 500 \
+ --enable-prefill-delayer \
+ --mem-fraction-static 0.65 \
+ --max-running-requests 36 \
+ --chunked-prefill-size -1 --max-prefill-token 150000 \
+ --cuda-graph-bs 8 16 24 32 40 \
+ --moe-a2a-backend ascend_fuseep --deepep-mode auto --quantization modelslim \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant \
+ --dtype bfloat16 \
+ --trust-remote-code \
+ --tokenizer-worker-num 8
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 32000 --random-input-len 65536 --random-output-len 1024 --num-prompts 144 --random-range-ratio 1 --max-concurrency 36
+```
+### MiniMax-M2.5 64K-1K High Throughput on A3 16 Cards Disaggregation Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 16Card
+
+DeployMode: PD Disaggregation
+
+Dataset: random
+
+Input Output Length: 64K+1K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+export SGLANG_SET_CPU_AFFINITY=1
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PATH=/usr/local/Ascend/8.5.0/compiler/bishengir/bin:$PATH
+
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+
+export ASCEND_MF_STORE_URL="tcp://your_prefill_ip:24667"
+
+P_IP=('your_prefill_ip')
+D_IP=('your_decode_ip')
+D_MASTER="${D_IP[0]}:8001"
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+LOCAL_HOST1=`hostname -I|awk -F " " '{print$1}'`
+LOCAL_HOST2=`hostname -I|awk -F " " '{print$2}'`
+
+# prefill
+for i in "${!P_IP[@]}";
+do
+ if [[ "$LOCAL_HOST1" == "${P_IP[$i]}" || "$LOCAL_HOST2" == "${P_IP[$i]}" ]];
+ then
+ echo "${P_IP[$i]}"
+ export HCCL_SOCKET_IFNAME=your_nic
+ export GLOO_SOCKET_IFNAME=your_nic
+ export ASCEND_USE_FIA=1
+ export HCCL_BUFFSIZE=2500
+ export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
+ export TASK_QUEUE_ENABLE=2
+ export DEEPEP_NORMAL_LONG_SEQ_ROUND=64
+ export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=2048
+ export DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ=1
+ python -m sglang.launch_server --model-path ${MODEL_PATH} --disaggregation-mode prefill --host ${P_IP[$i]} \
+ --port 32000 --disaggregation-bootstrap-port $((8998+$i)) --trust-remote-code --nnodes 1 --node-rank 0 \
+ --tp-size 16 --mem-fraction-static 0.43 --attention-backend ascend --device npu --quantization modelslim \
+ --disaggregation-transfer-backend ascend --max-running-requests 128 \
+ --chunked-prefill-size -1 --max-prefill-tokens 58000 --moe-a2a-backend deepep --deepep-mode normal \
+ --tokenizer-worker-num 16 \
+ --dp-size 2 --enable-dp-attention --dtype bfloat16 --load-balance-method round_robin \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant --skip-server-warmup
+ NODE_RANK=$i
+ break
+ fi
+done
+
+# decode
+for i in "${!D_IP[@]}";
+do
+ if [[ "$LOCAL_HOST1" == "${D_IP[$i]}" || "$LOCAL_HOST2" == "${D_IP[$i]}" ]];
+ then
+ echo "${D_IP[$i]}"
+ export HCCL_BUFFSIZE=1600
+ export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=640
+ export HCCL_SOCKET_IFNAME=your_nic
+ export GLOO_SOCKET_IFNAME=your_nic
+ export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+ export SGLANG_ENABLE_SPEC_V2=1
+ export SGLANG_NPU_FUSED_MOE_MODE=2
+ export SGLANG_DISAGGREGATION_NUM_PRE_ALLOCATE_REQS=96
+
+ python -m sglang.launch_server --model-path ${MODEL_PATH} --disaggregation-mode decode --host ${D_IP[$i]} \
+ --cuda-graph-bs 8 16 24 32 40 \
+ --port 33000 --trust-remote-code \
+ --tp-size 16 --mem-fraction-static 0.76 --attention-backend ascend --device npu --quantization modelslim \
+ --nnodes 1 --node-rank $i --dist-init-addr $D_MASTER \
+ --disaggregation-transfer-backend ascend --max-running-requests 80 \
+ --chunked-prefill-size -1 --moe-a2a-backend ascend_fuseep --deepep-mode low_latency \
+ --tokenizer-worker-num 16 \
+ --dp-size 2 --enable-dp-attention --dtype bfloat16 \
+ --load-balance-method round_robin \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 3 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 4 \
+ --speculative-draft-model-quantization unquant
+
+ NODE_RANK=$i
+ break
+ fi
+done
+```
+
+```shell Command
+python -m sglang_router.launch_router \
+ --pd-disaggregation \
+ --policy round_robin \
+ --prefill http://your_prefill_ip:32000 8998 \
+ --decode http://your_decode_ip:33000 \
+ --host 127.0.0.1 \
+ --mini-lb \
+ --port 6688
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 6688 --random-input-len 65536 --random-output-len 1024 --num-prompts 640 --random-range-ratio 1 --max-concurrency 160
+```
+### MiniMax-M2.5 128K-1K High Throughput on A3 16 Cards Disaggregation Mode
+
+Model: MiniMax-M2.5
+
+Hardware: Atlas 800I A3 16Card
+
+DeployMode: PD Disaggregation
+
+Dataset: random
+
+Input Output Length: 128K+1K
+
+#### Model Deployment
+
+```bash Command
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+export SGLANG_SET_CPU_AFFINITY=1
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+export PATH=/usr/local/Ascend/8.5.0/compiler/bishengir/bin:$PATH
+
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export STREAMS_PER_DEVICE=32
+
+export ASCEND_MF_STORE_URL="tcp://your_prefill_ip:24667"
+
+P_IP=('your_prefill_ip')
+D_IP=('your_decode_ip')
+D_MASTER="${D_IP[0]}:8001"
+MODEL_PATH=/path/to/MiniMax-M2.5-w8a8-QuaRot
+
+EAGLE_MODEL_PATH=/path/to/MiniMax-M2.5-eagle-model
+export PYTHONPATH=${EAGLE_MODEL_PATH}:$PYTHONPATH
+export SGLANG_EXTERNAL_MODEL_PACKAGE=custom_eagle3
+
+LOCAL_HOST1=`hostname -I|awk -F " " '{print$1}'`
+LOCAL_HOST2=`hostname -I|awk -F " " '{print$2}'`
+
+# prefill
+for i in "${!P_IP[@]}";
+do
+ if [[ "$LOCAL_HOST1" == "${P_IP[$i]}" || "$LOCAL_HOST2" == "${P_IP[$i]}" ]];
+ then
+ echo "${P_IP[$i]}"
+ export HCCL_SOCKET_IFNAME=your_nic
+ export GLOO_SOCKET_IFNAME=your_nic
+ export ASCEND_USE_FIA=1
+ export HCCL_BUFFSIZE=2500
+ export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
+ export TASK_QUEUE_ENABLE=2
+ export DEEPEP_NORMAL_LONG_SEQ_ROUND=64
+ export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=2048
+ export DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ=1
+ python -m sglang.launch_server --model-path ${MODEL_PATH} --disaggregation-mode prefill --host ${P_IP[$i]} \
+ --port 32000 --disaggregation-bootstrap-port $((8998+$i)) --trust-remote-code --nnodes 1 --node-rank 0 \
+ --tp-size 16 --mem-fraction-static 0.43 --attention-backend ascend --device npu --quantization modelslim \
+ --disaggregation-transfer-backend ascend --max-running-requests 128 \
+ --chunked-prefill-size -1 --max-prefill-tokens 130000 --moe-a2a-backend deepep --deepep-mode normal \
+ --tokenizer-worker-num 16 \
+ --dp-size 2 --enable-dp-attention --dtype bfloat16 --load-balance-method round_robin \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 2 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 3 \
+ --speculative-draft-model-quantization unquant --skip-server-warmup
+ NODE_RANK=$i
+ break
+ fi
+done
+
+# decode
+for i in "${!D_IP[@]}";
+do
+ if [[ "$LOCAL_HOST1" == "${D_IP[$i]}" || "$LOCAL_HOST2" == "${D_IP[$i]}" ]];
+ then
+ echo "${D_IP[$i]}"
+ export HCCL_BUFFSIZE=1600
+ export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=640
+ export HCCL_SOCKET_IFNAME=your_nic
+ export GLOO_SOCKET_IFNAME=your_nic
+ export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+ export SGLANG_ENABLE_SPEC_V2=1
+ export SGLANG_NPU_FUSED_MOE_MODE=2
+ export SGLANG_DISAGGREGATION_NUM_PRE_ALLOCATE_REQS=96
+
+ python -m sglang.launch_server --model-path ${MODEL_PATH} --disaggregation-mode decode --host ${D_IP[$i]} \
+ --cuda-graph-bs 2 4 8 \
+ --port 33000 --trust-remote-code \
+ --tp-size 16 --mem-fraction-static 0.76 --attention-backend ascend --device npu --quantization modelslim \
+ --nnodes 1 --node-rank $i --dist-init-addr $D_MASTER \
+ --disaggregation-transfer-backend ascend --max-running-requests 80 \
+ --chunked-prefill-size -1 --moe-a2a-backend ascend_fuseep --deepep-mode low_latency \
+ --tokenizer-worker-num 8 \
+ --dp-size 2 --enable-dp-attention --dtype bfloat16 \
+ --load-balance-method round_robin \
+ --speculative-algorithm EAGLE3 \
+ --speculative-draft-model-path $EAGLE_MODEL_PATH \
+ --speculative-num-steps 2 \
+ --speculative-eagle-topk 1 \
+ --speculative-num-draft-tokens 3 \
+ --speculative-draft-model-quantization unquant
+
+ NODE_RANK=$i
+ break
+ fi
+done
+```
+
+```shell Command
+python -m sglang_router.launch_router \
+ --pd-disaggregation \
+ --policy round_robin \
+ --prefill http://your_prefill_ip:32000 8998 \
+ --decode http://your_decode_ip:33000 \
+ --host 127.0.0.1 \
+ --mini-lb \
+ --port 6688
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving --dataset-name random --backend sglang --host 127.0.0.1 --port 6688 --random-input-len 131072 --random-output-len 1024 --num-prompts 192 --random-range-ratio 1 --max-concurrency 48
+```