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Best open-source LLM serving stack

4 models · updated 2026-07-11

The verdict

vLLM leads — All 4 models rank vLLM the top pick.

Combined ranking

  1. 1
    vLLMincumbent—20 pts
    GPT #1Claude #1Gemini #1Grok #1

    Best overall balance of throughput, broad model and hardware support, continuous batching, mature OpenAI-compatible serving, and a large production ecosystem

    To stay #1 Match SGLang’s efficiency on prefix-heavy and agentic workloads

  2. 2
    SGLang—16 pts
    GPT #2Claude #2Gemini #2Grok #2

    Exceptional throughput and latency, especially with shared prefixes, long contexts, structured generation, multimodal models, and RadixAttention caching

    To rank higher Broaden hardware support and deployment maturity beyond its strongest NVIDIA configurations

  3. 3
    TensorRT-LLMincumbent—12 pts
    GPT #3Claude #3Gemini #3Grok #3

    Often delivers the highest raw throughput and lowest latency on NVIDIA GPUs, with excellent quantization, speculative decoding, and multi-GPU optimization

    To rank higher Eliminate the compilation-heavy, NVIDIA-specific deployment complexity

  4. 4
    llama.cppincumbent—5 pts
    GPT #4Claude #4Gemini #5Grok —

    Unmatched portability across CPUs, GPUs, laptops, edge devices, and operating systems, with excellent GGUF quantization and a capable OpenAI-compatible server

    To rank higher Improve high-concurrency datacenter throughput to compete with vLLM and SGLang

  5. 5
    Ollama—4 pts
    GPT —Claude —Gemini #4Grok #4

    Commands the local and developer edge-serving space with its seamless command-line interface, model packaging, and easy API integration.

    To rank higher Support native multi-GPU distributed orchestration and high-concurrency production features.

  6. 6
    Hugging Face TGIincumbent—2 pts
    GPT —Claude #5Gemini —Grok #5

    Production-hardened and the easiest path from Hugging Face Hub to a served endpoint — solid continuous batching, quantization support, clean Docker deployment, and Apache 2.0 licensing restored trust

    To rank higher Regain performance leadership — development pace and benchmark results have fallen behind vLLM and SGLang, making it the convenience pick rather than the fast one.

  7. 7
    LMDeploy—1 pts
    GPT #5Claude —Gemini —Grok —

    Strong NVIDIA serving performance, efficient TurboMind kernels, practical quantization, OpenAI-compatible APIs, and especially good support for the Qwen ecosystem

    To rank higher Expand model coverage, hardware portability, and community adoption to vLLM levels

By model

ChatGPT

  1. 1.vLLM
  2. 2.SGLang
  3. 3.TensorRT-LLM
  4. 4.llama.cpp
  5. 5.LMDeploy

Claude

  1. 1.vLLM
  2. 2.SGLang
  3. 3.TensorRT-LLM
  4. 4.llama.cpp
  5. 5.Hugging Face TGI

Gemini

  1. 1.vLLM
  2. 2.SGLang
  3. 3.TensorRT-LLM
  4. 4.Ollama
  5. 5.llama.cpp

Grok

  1. 1.vLLM
  2. 2.SGLang
  3. 3.TensorRT-LLM
  4. 4.Ollama
  5. 5.Hugging Face TGI

Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled continuously