RUNTIME / ADVANCED
SGLang
Multi-request GPU serving with prefix caching and speculative decoding
一手来源DifficultyAdvancedSetup profile
Platforms4nvidia · amd · intel · cpu
APIOpenAI-compatible + native runtime API:30000
01 / INSTALL & RUN
安装方式取决于操作系统。以下命令是示例或模板,请先替换占位符并核对量化版本、文件格式、驱动和运行时支持;内存适配不保证部署成功。
- 1Install
pip install uv && uv pip install --prerelease=allow sglang - 2Start a model
python3 -m sglang.launch_server --model-path <verified-checkpoint> --port 30000 - 3Connect your app
OpenAI-compatible + native runtime API · :30000. Keep the service bound to localhost unless you add authentication and network controls.
注意
Each platform is a separate lane with its own floors: the NVIDIA lane requires CUDA 13, and 0.5.19 was the last CUDA 12 release. ROCm, Intel XPU, Xeon CPU and Apple Metal are documented separately, so support on one lane is not proof for another.
02 / COMPATIBLE MODELS
代表性开放权重模型
Alibaba Qwen
Qwen3.6 27B
27BQ4 / NVFP4 estimate
- 估算内存
- ~18.5 GB
- 上下文
- 262K native
Alibaba Qwen
Qwen3.8 27B
27BQ4 estimate
- 估算内存
- ~19.5 GB
- 上下文
- 262K native
Alibaba Qwen
Qwen3.6 35B-A3B
35B3B active · Q4 / NVFP4 MoE
- 估算内存
- ~25 GB
- 上下文
- 262K native
DeepSeek
DeepSeek V4 Flash
284B13B active · Official FP4 + FP8 mixed
- 估算内存
- ~176 GB
- 上下文
- 1M native
Google
Gemma 3 1B
1BINT4 / GGUF Q4
- 估算内存
- ~1.4 GB
- 上下文
- 32K
Meta
Llama 3.2 3B
3BGGUF Q4
- 估算内存
- ~2.8 GB
- 上下文
- 128K