ModelTC/LightLLM

Health v2 · maintenance only

Adoption not part of the score

4317 stars · 370 forks observed · 2026-10-10

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

LightLLM is a Python-based LLM inference and serving framework designed for lightweight deployment, easy scalability, and high throughput. It provides an OpenAI-compatible API server for serving models like LLaMA and DeepSeek, leveraging techniques from FasterTransformer, TGI, vLLM, and FlashAttention.

Use cases

• serve an LLM behind an OpenAI-compatible API
• deploy DeepSeek-R1 on a single GPU machine with maximum throughput
• self-host a lightweight alternative to vLLM or TGI
• run LLM inference with high concurrency and low latency
• serve LLaMA-family models in production
• benchmark LLM serving performance on NVIDIA GPUs

When to choose

• you need a lightweight, high-performance LLM serving server on NVIDIA GPUs
• you want an OpenAI-compatible endpoint for self-hosted models
• you need fast DeepSeek or LLaMA serving with advanced scheduling and KV cache features

When to avoid

• you need CPU-only or non-NVIDIA hardware inference
• you want a full training or fine-tuning framework rather than inference serving
• you need broad multi-modal model support beyond text LLMs

Facets

service · maturity active

llm-inference http-server api-framework gpu-computing large-language-models artificial-intelligence deep-learning developer-tools python self-hosted llm-serving openai-compatible-api inference-server vllm-alternative flashattention triton model-deployment high-performance natural-language-processing linux gpu docker

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markdown · JSON · MCP: product_card(name="ModelTC/LightLLM")