Individual skill
inference-serving-sglang
Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.
cli-tool/components/skills/ai-research/inference-serving-sglang/SKILL.md
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- anthropic Repository topic
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- inference-serving Declared skill tag
- sglang Declared skill tag
- structured-generation Declared skill tag
- radixattention Declared skill tag
- prefix-caching Declared skill tag
- constrained-decoding Declared skill tag
- agents Declared skill tag
- json-output Declared skill tag
- fast-inference Declared skill tag
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# SGLang
High-performance serving framework for LLMs and VLMs with RadixAttention for automatic prefix caching.
## When to use SGLang
**Use SGLang when:**
- Need structured outputs (JSON, regex, grammar)
- Building agents with repeated prefixes (system prompts, tools)
- Agentic workflows with function calling
- Multi-turn conversations with shared context
- Need faster JSON decoding (3× vs standard)
**Use vLLM instead when:**