LM Studio vs. vLLM Comparison


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Requests can be approved through the portal, the mobile app, or the API. Files receive an OPSWAT MetaDefender reputation check before elevation, and software that has already been vetted can clear automatically through pre-approval or the AI and Machine Learning approval engine. A single agent supports Windows, macOS, and Linux and behaves the same whether the endpoint is online or offline. Auditing and inventory are included as standard. 105 Ratings Visit Website JDisc Discovery JDisc Discovery is a comprehensive network inventory and IT asset management solution designed to help organizations gain clear, up-to-date visibility into their IT environment. It automatically scans and maps devices across the network, including servers, workstations, virtual machines, and network hardware, to create a detailed inventory of all connected assets. This includes critical information such as hardware configurations, software installations, patch levels, and relationshipots between devices. 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About Use models through the in-app Chat UI or an OpenAI-compatible local server. Minimum requirements: M1/M2/M3 Mac, or a Windows PC with a processor that supports AVX2. Linux is available in beta. One of the main reasons for using a local LLM is privacy, and LM Studio is designed for that. Your data remains private and local to your machine. You can use LLMs you load within LM Studio via an API server running on localhost.	About vLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Individuals wanting a desktop application for running local LLMs on their computer	Audience AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Supported Online Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing No information available. Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information LM Studio lmstudio.ai	Company Information vLLM United States vllm.ai
Alternatives Agnai	Alternatives LocalAI
Atomic Chat	Ollama
Backyard AI	OpenVINO Intel
Cheaper Inference Keak	Wafer
OpenRouter View All	NVIDIA TensorRT NVIDIA View All
Categories AI Gateways Supported AI Inference Supported Artificial Intelligence Supported	Categories AI Inference Supported

Integrations Hugging Face Supported OpenAI Supported omp Supported Agent Zero Supported Broxi AI Supported Database Mart Not Supported Devstral Supported KServe Not Supported LM Studio Bionic Supported Linkly AI Supported Llama 2 Supported MachinesFluent Supported Melaya Supported NGINX Not Supported NVIDIA Personal AI Router (PAIR) Supported Osaurus Supported PyTorch Not Supported Spacesuit Supported StarCoder Supported oMLX Supported Show More Integrations View All 29 Integrations	Integrations Hugging Face Supported OpenAI Supported omp Supported Agent Zero Not Supported Broxi AI Not Supported Database Mart Supported Devstral Not Supported KServe Supported LM Studio Bionic Not Supported Linkly AI Not Supported Llama 2 Not Supported MachinesFluent Not Supported Melaya Not Supported NGINX Supported NVIDIA Personal AI Router (PAIR) Not Supported Osaurus Not Supported PyTorch Supported Spacesuit Not Supported StarCoder Not Supported oMLX Not Supported Show More Integrations View All 11 Integrations
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