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Ollama

Get up and running with large language models locally. Run, create, and share large language models.

Introduction

Ollama lets you run large language models locally. It bundles model weights, configuration, and code into a single package, defined by a Modelfile. Key features include:

  • Local Execution: Run LLMs directly on your machine, ensuring data privacy and low latency.
  • Modelfiles: Define custom models using a simple, human-readable format.
  • Cross-Platform Support: Available for macOS, Windows, and Linux.
  • Model Sharing: Easily share and distribute models with others.

Use cases:

  • Local AI Development: Develop and test AI applications without relying on cloud services.
  • Privacy-Focused Applications: Build applications that require data to stay on-premises.
  • Offline Access: Use LLMs in environments with limited or no internet connectivity.
  • Custom Model Creation: Create and share your own specialized language models.

Alternatives

  • LM Studio

    LM Studio provides a user-friendly desktop application for discovering, downloading, and running large language models locally on your computer.

  • Jan

    Jan offers an open-source, privacy-focused desktop application to run large language models locally, similar to Ollama but with a different interface.

  • LocalAI

    LocalAI delivers a drop-in replacement for OpenAI API that allows you to run LLMs and other models locally or on your own infrastructure.

  • llama.cpp

    llama.cpp serves as the foundational C/C++ library for efficient inference of LLaMA models and derivatives directly on your CPU, which many other tools build upon.

  • Text Generation WebUI (oobabooga)

    Text Generation WebUI provides a comprehensive web-based interface for loading, configuring, and interacting with various local large language models.

  • Hugging Face Transformers

    Hugging Face Transformers offers a vast library and ecosystem for easily downloading, fine-tuning, and running a wide array of pre-trained models, including LLMs, locally.

  • vLLM

    vLLM focuses on high-throughput and low-latency inference for large language models, making it an excellent choice for self-hosting performant LLM APIs.

  • RunPod

    RunPod offers on-demand GPU cloud infrastructure, allowing users to rent powerful machines to run and manage their own LLMs without local hardware constraints.

  • Replicate

    Replicate provides an API for running open-source machine learning models, including many LLMs, simplifying deployment and scaling without managing infrastructure.

  • NVIDIA TensorRT-LLM

    NVIDIA TensorRT-LLM optimizes and accelerates large language model inference on NVIDIA GPUs, providing a high-performance solution for local or self-hosted deployments.

User Reviews

4.5/5.0
(11reviews)
Click stars to rate

Pricing

Pricing Model: Freemium

Free

Entry-level plan providing access to Ollama's cloud models.

$0
N/A

Pro

Intermediate plan offering higher usage limits for cloud models.

$20/mo
monthly

Max

Premium plan providing the highest usage limits for cloud models.

$100/mo
monthly

FAQ

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