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sglang

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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.

When to use

• 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)
• Simple text generation without structure
• Don't need prefix caching
• Want mature, widely-tested production system

When not to use

• simple text generation without structure
• no need for prefix caching
• maximum single-request latency (no batching needed)
• NVIDIA-only deployment
• FP8/INT4 quantization on H100

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