sglang_v0.5.2/sglang/docs/basic_usage/qwen3.md

Qwen3-Next Usage

SGLang has supported Qwen3-Next-80B-A3B-Instruct and Qwen3-Next-80B-A3B-Thinking since this PR.

Launch Qwen3-Next with SGLang

To serve Qwen3-Next models on 4xH100/H200 GPUs:

python3 -m sglang.launch_server --model Qwen/Qwen3-Next-80B-A3B-Instruct --tp 4

Configuration Tips

• --max-mamba-cache-size: Adjust --max-mamba-cache-size to increase mamba cache space and max running requests capability. It will decrease KV cache space as a trade-off. You can adjust it according to workload.
• --mamba-ssm-dtype: bfloat16 or float32, use bfloat16 to save mamba cache size and float32 to get more accurate results. The default setting is float32.

EAGLE Speculative Decoding

Description: SGLang has supported Qwen3-Next models with EAGLE speculative decoding.

Usage: Add arguments --speculative-algorithm, --speculative-num-steps, --speculative-eagle-topk and --speculative-num-draft-tokens to enable this feature. For example:

python3 -m sglang.launch_server --model Qwen/Qwen3-Next-80B-A3B-Instruct --tp 4 --speculative-num-steps 3  --speculative-eagle-topk 1  --speculative-num-draft-tokens 4 --speculative-algo NEXTN

Details can be seen in this PR.