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Ollama, llama.cpp or vLLM: pick by workload, not by benchmark Tags:llm, localllm, performance, ai

Every few weeks a new benchmark says one local inference stack is X% faster than another. The numbers are usually real. They're also usually answering a different question than the one you have.

  • Ollama best for experimentation with easy setup and default settings
  • llama.cpp optimal for single machine maximum token throughput with hardware-specific tuning
  • vLLM ideal for concurrent request handling with continuous batching and paged KV cache

Who owns the LLM? 28 AIOps products compared

If you build AI features for an AIOps product, a customer will ask "can we use our own LLM?" sooner or later. What they want is clear: keep the data private and under their control, and still get…

  • Only 13 AIOps products offer no control over the LLM model.
  • 10 products ship a default model with user plug-in capability.
  • 3 products are open source, allowing customers to bring their own models.

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