Best llm to run locally.

• Best llm to run locally ” PydanticAI – “Python Agent Framework designed to make it less painful to build production grade applications with Generative AI. cpp: LLaMa. q4_K_M. 7B-v1. Nov 19, 2024 · First let me tell you what is the best Mac model with Apple Silicone for running large language models locally. g. That's really the best LLM I can run on my system. I'm looking to design an app that can run offline (sort of like a chatGPT on-the-go), but most of the models I tried (H2O. H2O LLM Studio. However, I wanted to be able to run LLMs locally, just for fun. NET library to run LLM (🦙LLaMA/LLaVA) on Feb 27, 2025 · Discover the top 5 LLM tools to run models locally—Llama. Figuring out what hardware requirements I need for that was complicated. It’s known for its minimal setup and excellent performance across various hardware, making it a popular choice for developers looking to run LLMs locally. Ready to Dive Into Local LLMs? If you're new to running LLMs locally, we recommend starting with GPT4All or LM Studio for the easiest user experience. 6 days ago · A GUI for downloading and running GGUF models (no Docker needed, but a solid alternative for desktop users). I suspect I'll get around 5 running Goliath 120b, which is fast enough to be usable. For reference I'm running a dedicated P40, so I can fit some larger models, but still have found Mistral 7b far more pleasant to work with, while leaving plenty of space for running other models side by side with it (stabe diffusion, bark) And then there is of course Horde where you can run on the GPU of a volunteer with no setup whatsoever. Dec 2, 2020 · I got the mini with 14 CPU cores, 20 GPU cores, 64 GB of RAM, and 2TB of storage. To use LM Studio, visit the link above and download the app for your machine. As a C# developer I do have a fair bit of understanding of technology. May 7, 2024 · The nomic-ai/gpt4all is an LLM framework and chatbot application for all operating systems. Read the first two parts here: Mar 12, 2024 · An Ultimate Guide to Run Any LLM Locally. I was using a T560 with 8GB of RAM for a while for guanaco-7B. On the first run, the Sep 24, 2024 · Without adequate hardware, running LLMs locally would result in slow performance, memory crashes, or the inability to handle large models at all. What is … Ollama Tutorial: Your Guide to running LLMs Locally Read More » Best LLM to run locally . It’s quick to install, pull the LLM models and start prompting in your terminal / command prompt. On a totally subjective speed scale of 1 to 10: 10 AWQ on GPU 9. 0 is a large general language model pushing the limits of what can run locally on consumer hardware. It supports a wide range of frameworks, including PyTorch and TensorFlow, and allows for hardware acceleration, making it one of the best tools for running larger, more complex models locally. Developed by Google, local-llm is a tool designed to run LLMs on local machines or cloud workstations using CPU and memory instead of GPUs. In that case, probably your best bet would probably be more RAM, but you might want to wait and see how it develops. cpp cater to privacy-focused and lightweight needs. Mar 21, 2024 · Discover how to run Generative AI models locally with Hugging Face Transformers, gpt4all, Ollama, localllm, and Llama 2. The only thing I setup is "use 8bit cache" because I test it on Nov 2, 2024 · Below are two links that can help kickstart your search for your personal best LLM: Top 5 AI Models YOU Can Run Locally on YOUR Device! LLM Explorer; Conclusion. This makes it particularly appealing to AI developers, researchers, and businesses concerned with data control and privacy. , 8-bit integers). It supports various models, including LLaMA and PaLM. Hardware Requirements: For the 7B Model: 8GB+ VRAM; For the 13B Model: 16GB+ VRAM; How to Run: To deploy it, use text-generation-webui or Ollama. Apr 21, 2024 · The strongest open source LLM model Llama3 has been released, some followers have asked if AirLLM can support running Llama3 70B locally with 4GB of VRAM. Running LLMs locally is the easiest way to protect your privacy, but traditional LLMs are restricted to answering certain types of questions to reduce LLM abuse. Running LLMs locally is no longer just for experts. rn. If you’d like to run LLMs locally, and migrate to the cloud later, this could be a good tool for you. That’s where Docker Model Runner comes in. Dec 4, 2024 · Even though running models locally can be fun, you might want to switch to using an LLM hosted by a third party later to handle more requests. 0 (7 to 34B)Phind-CodeLlama-34B Nov 21, 2024 · 10+ Best LLM Tools To Run Models Locally 1. Yesterday I even got Mixtral 8x7b Q2_K_M to run on such a machine. What It Is Ollama targets macOS users, providing a simple tool to run LLMs (often variants of Llama 2 Oct 15, 2024 · Alright, let’s talk about the best Local LLM tools out there—because let’s face it, not all of us are into sending our precious data into the cloud, especially when we can keep things local and still get stuff done. Large language model runner Usage: ollama [flags] ollama [command] Available Commands: serve Start ollama create Create a model from a Modelfile show Show information for a model run Run a model pull Pull a model from a registry push Push a model to a registry list List models ps List running models cp Copy a model rm Remove a model help Help about any command Flags: -h, --help help for ollama Guys so I am thinking about creating some guide how to install and deal with local LLMs. Hugging Face also provides transformers, a Python library that streamlines running a LLM locally. In the wake of ChatGPT’s debut , the AI landscape has undergone a seismic shift. If 1b models are amazingly strong at their task, (such as phi-1 claims to be) using individual small expert models at 4bit at >7t/s with RAM wiggle-room is the best situation for LLMs on a phone. Run your own chatbot on a budget. And finally, here are the tools you can use to quickly deploy these local LLM models on your Mar 16, 2025 · Running an LLM locally provides greater privacy, reduced latency, and improved cost efficiency. From now on, each time you want to run your local LLM, start KoboldCPP with the saved config. Running language models locally on user devices. No Jul 26, 2024 · Explore our guide to deploy any LLM locally without the need for high-end hardware. Basically, you simply select which models to download and run against on your local machine and you can integrate directly into your code base (i. Jan 7, 2024 · Using llamafile, we can distribute and run LLMs with a single executable file, making them significantly more accesible. ai, Dolly 2. Apr 11, 2024 · It supports various backends including KoboldAI, AI Horde, text-generation-webui, Mancer, and Text Completion Local using llama. , which makes it easier to build LLM apps on open-source LLMs. As developers, we’ve embraced LLMs to help us code faster, allowing the LLM to generate the code it can write, so that we can focus on the code only we humans can write. cpp, and Hugging Face Transformers. py Feb 20, 2025 · The ability to run these models locally — whether on modest CPU setups or more powerful GPU systems — opens possibilities for developers, businesses, and individuals to harness AI’s power Mar 11, 2024 · If you let me know what settings / template you used for this test, I'll run a similar test on my M4 iPad with 16GB Ram. Dec 16, 2023 · Not sure if this question is bad form given HF sells compute, but here goes… I tried running Mistral-7B-Instruct-v0. In the current landscape of AI applications, running LLMs locally on CPU has become an attractive option for many developers and organizations. I compared some locally runnable LLMs on my own hardware (i5-12490F, 32GB RAM) on a range of tasks here… Jun 18, 2024 · Fortunately, Hugging Face regularly benchmarks the models and presents a leaderboard to help choose the best models available. Whether you’re a developer, writer, researcher, or hobbyist, local AI gives you freedom, security, and unlimited access – without relying on big tech. Feb 28, 2025 · It's best suited for chatbot apps and to generate dialogue-based experiences. This tutorial should serve as a good reference for anything you wish to do with Ollama, so bookmark it and let’s get started. I tried TheBloke's GPTQ and GGUF (4bit) versions. Mar 12, 2024 · There are many open-source tools for hosting open weights LLMs locally for inference, from the command line (CLI) tools to full GUI desktop applications. This guide provides recommendations tailored to each GPU's VRAM (from RTX 4060 to 4090), covering model selection, quantization techniques (GGUF, GPTQ), performance expectations, and essential tools like Ollama, Llama. Following the documentation, we will be using llava-v1. I don't know why people are dumping on you for having modest hardware. Feb 6, 2024 · This repository provides a comprehensive framework and tools to run LLMs locally on CPU and memory, right within the Google Cloud Workstation, using this method (though you can also run LLM models on your local machine or anywhere with sufficient CPU). Mar 11, 2025 · When I talk about running an LLM locally, I mean that I’m running a temporary instance of a model on my development machine. The Tech Robot offers the best Dec 16, 2024 · In this blog post, we’ll explore what Local LLMs are, the best options available, their requirements, and how they integrate with modern tools like LangChain for advanced applications. Here, I’ll outline some popular options Feb 14, 2025 · In this guide, we’ll explore how to run an LLM locally, covering hardware requirements, installation steps, model selection, and optimization techniques. You can even run LLMs on phones. Given the gushing praise for the model’s performance vs it’s small size, I thought this would work. LM Studio is a tool designed to run any model file with the format gguf. So what are the best available and supported LLM's that I can run and train locally without the need for a PhD to just get them setup? Running an LLM locally requires a few things: Open-source LLM: An open-source LLM that can be freely modified and shared ; Inference: Ability to run this LLM on your device w/ acceptable latency; Open-source LLMs Users can now gain access to a rapidly growing set of open-source LLMs. I prefer to chat with LLMs in my native language German, in addition to English, and few local models can do that as well as those from Mistral and Cohere. 1, Mistral & Gemma. With 7 layers offloaded to GPU. A useful general heuristic for selecting model sizes from Ollama’s README: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models. Realistically if you want to run the "full" models, you'd need more. Here are the top 6 tools for running LLMs locally: 1. Why Use LLMs Locally? Mar 26, 2025 · 16 Tools to Run LLMs Locally 1. cpp, GPT4All, LM Studio, Ollama, and Jan. ” OpenAI Swarm via ollama-swarm. These aren’t your average chatbots – they’re powerful tools that put the control in your hands. Per the title, I’m looking to host a small finetuned LLM on my local hardware. You’ll need a Windows PC with an Nvidia GeForce RTX 30 Series or higher GPU with at least 8GB of I have a laptop with a 1650 ti, 16 gigs of RAM, and an i5-10th gen. It supports gguf files from model providers such as Llama 3. Nov 5, 2024 · Fine-tuning requires even more GPU memory and ideally should be done on dedicated hardware so that it does not affect the LLM service for regular users. LM Studio can run any model file with the format gguf. To submit a query to a local LLM, enter the command llm install model-name. 55 bpw quant of llama 3 70B at 11 t/s. We can run an LLM locally, which has many great benefits, such as keeping the data local to your environment, either in the home network or home lab environment. Here we go. That's why I've created the awesome-local-llms GitHub repository to compile all available options in one streamlined place. In that case, you would need uncensored LLMs that you can run locally on Mar 12, 2024 · You can run simple inferences in the terminal by running: ollama run llama2. Jul 26, 2023 · Meta just released Llama 2 [1], a large language model (LLM) that allows free research and commercial use. Models with more B's (more parameters) will usually be more accurate and more coherent when following instructions but they will be much slower. ONNX (Open Neural Network Exchange) ONNX is a format for deep learning models that enables them to be executed locally, either on CPU or GPU. This allows them to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Ollama Feb 1, 2024 · At the time of writing this, I had a MacBook M1 Pro with 32GB of RAM, and I couldn’t run dolphin-mixtral-8x7b because it requires at least 64GB of RAM and I ended up running llama2-uncensored:7b While you can run any LLM on a CPU, it will be much, much slower than if you run it on a fully supported GPU. cpp) format, as well as in the MLX format (Mac only). It’s also private, offline, unlimited, and registration-free. Comparatively that means you'd be looking at 13gb vram for the 13b models, 30gb for 30b models, etc. Here are the top 8 tools that let you run Local LLMs on your machine, whether you’re team Mac, Windows, or Linux. The following example uses the library to run an older GPT-2 microsoft/DialoGPT-medium model. 5 is a perfect fit for the article “Best Local Vision LLM (Open Source)” due to its open-source nature and its advanced capabilities in local vision tasks. Best Uncensored LLM Model. Jan 24, 2025 · LM Studio is a user-friendly desktop application designed for downloading, managing, and running local LLMs. As we said, these models are free and made available by the open-source community. It provides a user-friendly interface for configuring and experimenting with LLMs. llm run TheBloke/Llama-2-13B-Ensemble-v5-GGUF 8000 python3 querylocal. May 15, 2025 · By running an LLM locally, you have the freedom to experiment, customize, and fine-tune the model to your specific needs without external dependencies. This means that varying CPUs end up putting out pretty similar results to each other because we don't have the same variety in RAM speeds and specifications that we do in processors. I’d say realistically, the 13-20b range is about as high as you can go while leaving room for other tasks. I get wildly different tok/s depending on which LLM and which template I'm using now. I would like to make it accessible via API to other applications both in and outside of my LAN, preferably with some sort of authentication mechanism or IP whitelisting. Running an LLM locally requires a few things: Open-source LLM: An open-source LLM that can be freely modified and shared; Inference: Ability to run this LLM on your device w/ acceptable latency; Open-source LLMs Users can now gain access to a rapidly growing set of open-source LLMs. It’s experimental, so users may lose their chat histories on updates. However, GPU offloading uses part of the LLM on the GPU and part on the CPU. This is not intended to be advice on self-hosting an AI application. May 13, 2025 · Running Large Language Models (LLMs) locally isn’t just about convenience; it’s about privacy, cost savings, and tailoring AI to fit your exact needs. Ollama: A command-line tool that allows you to run LLMs locally with minimal setup. As of this writing they have a ollama-js and ollama-python client libraries that can be used with Ollama installed on your dev machine to run local prompts. Alternatively, people run the models through their cpu and system ram. It’s a state-of-the-art model that combines a vision encoder and Vicuna for general-purpose visual and language understanding. H2O LLM Studio: Feb 11, 2025 · LM Studio stands out with its user-friendly interface, making it accessible even for those new to running LLMs locally. Jul 14, 2024 · Running LLMs locally is the easiest way to protect your privacy, but traditional LLMs are restricted to answering certain types of questions to reduce LLM abuse. 7bCodeQwen1. With that in mind, I'm planning to run 4 3090s because they're relatively cheap used at the moment, and they have the same vram as the 4090. I do not expect to ever have more than 100 users, so I’m not super concerned about scalability. I don't use that for work though. cpp is a lightweight and efficient tool for locally running large language models (LLMs). Let’s be clear. /llm-tool/. I run LLaMa3 70b locally on a pricy mac. With Apple Silicon’s improved architecture and unified memory, running local Large Language Models (LLMs) on the M4 Mac Mini is not only possible but surprisingly efficient. If you already Oct 23, 2024 · The most accurate LLMs, designed to run in the data center, are tens of gigabytes in size, and may not fit in a GPU’s memory. Mar 21, 2025 · Running an LLM locally has significant advantages over cloud-based solutions, including greater security, lower latency, and, in some cases, better performance, depending on the system hardware Mar 3, 2025 · Although powerful cloud-based LLM services exist, many users and organizations prefer running these models locally for reasons like data privacy, latency, or custom fine-tuning. When evaluating the price-to-performance ratio, the best Mac for local LLM inference is the 2022 Apple Mac Studio equipped with the M1 Ultra chip – featuring 48 GPU cores, 64 GB or 96 GB of RAM with an impressive 800 GB/s bandwidth. 1, Phi 3, Mistral, and Gemma. I also would prefer if it had plugins that could read files. I guess V3 will be even better (will probably switch to it once it has private api access), Qwen 32B Instruct performs worse in Polish that Aya. Use llama. ggmlv3. I run Stable Diffusion and ComfyUI locally and have turned that into a side gig. If your desktop or laptop does not have a GPU installed, one way to run faster inference on LLM would be to use Llama. Moreover, how does Llama3’s performance compare to GPT-4? Sep 1, 2024 · I do use the larger bit quantized models for more accuracy and less hallucinations. Mar 16, 2025 · If you’re searching for the smallest LLM to run locally, the best options depend on your hardware and use case: For ultra-low memory usage → BERT Mini or GPT-2 Small; For general NLP tasks → TinyLlama or DistilGPT-2; For speech recognition → Whisper Small; For text generation → DistilGPT-2 or GPT-2 Small May 1, 2025 · Description: SOLAR-10. This comprehensive guide explains how to set up, experiment, and integrate local LLMs while ensuring data privacy and optimizing performance. It’s now accessible enough to run a LLM on a Raspberry Pi smarter than the original ChatGPT (November 2022). Oct 8, 2024 · Some of the best LLM tools to run models locally include: LM Studio: A GUI-based tool that supports various models, including Llama 3. Exo, Ollama, and LM Studio stand out as the most efficient solutions, while GPT4All and Llama. Organizations can also deploy language models directly on end-user devices using specialized tools and services that support local LLM use. nous-capybara-34b I haven't been able to use that with my 3090Ti yet. gpt-4o smokes and is cheap. We have been using them in our beginner-friendly crash course on building RAG systems. Here are 5 lightweight LLMs you can run on very low-power hardware. 5 GGML on GPU (cuda) 8 GGML on GPU (Rocm) Apr 4, 2025 · At the same time, more and more developers want the flexibility to run LLMs locally for development, testing, or even offline use cases. Deepseek V2 was better but it's too big to run reliably locally. Nov 10, 2024 · Over the past month I’ve been exploring the rapidly evolving world of Large Language Models (LLM). , 32-bit floating-point) to lower precision formats (e. 24GB is the most vRAM you'll get on a single consumer GPU, so the P40 matches that, and presumably at a fraction of the cost of a 3090 or 4090, but there are still a number of open source models that won't fit there unless you shrink them considerably. As of right now, with the fine-tuned LLM and the "TinyLLaMa 1B" template being used I get the following: Run those on GPU and you can have much larger models run with decent performance and relatively little VRAM. Jan 29, 2025 · Nexa. Jul 18, 2024 · Before we explore further how to run models, let’s take a closer look at quantization – a key technique that makes local LLM execution possible on standard hardware. In this guide, we’ll explore the 10 best tools to run LLMs locally in 2025, perfect for anyone looking to stay ahead in the AI game. cpp is the backend technology that powers many local LLM tools. Punches way above it's weight so even bigger local models are no better. no time to wait on a quantized version of the model at 5 or 6 tps. Apr 18, 2024 · Large language models (LLMs) are a type of artificial intelligence (AI) that are trained on massive datasets of text and code. Running LLM's locally on a phone is currently a bit of a novelty for people with strong enough phones, but it does work well on the more modern ones that have the ram. The answer is YES. Here's a general outline of the steps: Install Cline: Install the Cline extension from the VS Code marketplace . As for the model's skills, I don't need it for character-based chatting. bin inference, and that worked fine. May 20, 2024 · Related: 3 Open Source LLM With Longest Context Length Jan is an open-source, self-hosted alternative to ChatGPT, designed to run 100% offline on your computer. Thus you will be more limited in speed and what you can run compared to other options. For work, we're hitting api's. By running models locally, you maintain full data ownership and avoid the potential security risks associated with cloud Jan 2, 2025 · How to run an LLM locally on macOS (Image credit: Future) Mac users with Apple Silicon (M1/M2/M3) chips have great options for running language models (LLMs) locally. I tried running locally following these lines of code: # Install the tools pip3 install openai pip3 install . With Ollama, LM Studio, and GPT4All, anyone can now harness private, uncensored AI on their own machine. I'm really glad I didn't go for a model with less memory because I wouldn't have been able to run large language models locally. Im trying to run mixtral-7x8b-instruct localy but lack the compute power, I looked on Runpod. ” Feb 4, 2025 · This tells Cline to use your locally running DeepSeek R1 instance via Ollama. 🔥 Run multiple models with LlamaEdge! As a bonus, Linux by itself easily gives you something like 10-30% performance boost for LLMs, and on top of that, running headless Linux completely frees up the entire VRAM so you can have it all for your LLM in its entirety, which is impossible in Windows because Windows itself reserves part of the VRAM just to render the desktop. Or you might have a team developing the user-facing parts of an application with an API while a different team builds the LLM inference infrastructure separately. Qwen2 came out recently but it's still not as good. When running local LLMs in a CPU-bound manner like I'm going to show, the main bottleneck is actually RAM speed. Slow though at 2t/sec. You can run any compatible Large Language Model (LLM) from Hugging Face, both in GGUF (llama. Apr 17, 2025 · Discover the optimal local Large Language Models (LLMs) to run on your NVIDIA RTX 40 series GPU. Feb 19, 2025 · The M4 Mac Mini has quickly become a go-to option for developers and AI enthusiasts looking for a compact yet powerful machine. This report aims to provide users with limitations an opportunity to taste and experience running modules locally for a valuable learning experience. Sort by: For hardware I use a 4090, which allows me to run a 2. It seems impracticall running LLM constantly or spinning it off when I need some answer quickly. Quite honestly I'm still new to using local LLMs so I probably won't be able to offer much help if you have questions - googling or reading the wikis will be much more helpful. Currently getting about 11-12 t/s running a 70b GGUF model, which has been enjoyable. Let’s see how we can run a local LLM model to host our own private local AI server, using large language models. Tools for Running Local LLMs. The LLM space is growing rapidly, with new LLMs or updated models appearing almost weekly. To run an LLM locally, we will need to download a llamafile – here, the bundled LLM is meant – and execute it. For my own personal use, Command R+ is the best local model since Mixtral 8x7B, and I've been using either since their release. Nov 11, 2024 · Using an LLM locally was simple, wasn't it? That said, Ollama elegantly integrates with almost all LLM orchestration frameworks like LlamaIndex, Langchain, etc. Gpt4All – “Free-to-use, locally running, privacy-aware chatbot. May 15, 2025 · Choosing the best local LLM for coding depends on your hardware, use case, and preferred programming languages. Check it out! We’re diving into some awesome open-source, uncensored language models. Running the best LLM models to run locally gives tech-savvy beginners AI capabilities (writing, coding, analysis) without relying on the cloud. ChatterUI is linked to the ggml library and can run LLaMA models locally. I have the most current text-generator-webui and just load the network `turboderp_Mixtral-8x7B-instruct-exl2_3. First, however, a few caveats—scratch that, a lot of caveats. 5 for free and 4 for 20usd/month? My story: For day to day questions I use ChatGPT 4. Recommended Hardware for Running LLMs Locally. It offers enhanced productivity through customizable AI assistants, global hotkeys, and in-line AI features. This is the most beginner-friendly and simple method of downloading and running LLMs on your local machines. 5 GPTQ on GPU 9. ⭐ Like our work? Give us a star! 📖 Checkout our official docs and a Manning ebook on how to customize open source models. io and Vast ai for servers but they are still pretty pricey. That stuff is super experimental right now but it wouldn't surprise me if it's mainstream in six weeks. The Best Local LLM for Coding The best local large language models (LLMs) for coding provide privacy, offline access, customization, and cost savings while delivering strong code generation and debugging capabilities. Dec 23, 2024 · Unlike other tools, chatd comes with a built-in LLM runner, so you don’t need to install anything extra, just download, unzip, and run the executable. I am currently contemplating buying a new Macbook Pro as my old Intel-based one is getting older. 70b+: Llama-3 70b, and it's not close. Question | Help Hi, new here I was wondering which is the most competent LLM that I can run locally. I created this blog post as a helping guide for others who are in a similar situation like myself. 88 votes, 32 comments. A modest desktop or laptop supports even smarter AI. Yes, my models speak with me in conversation! Also I like LM Studio. 5bpw`. LLM training optimized: OpenLLaMa [^5^] 2023: Running local LLMs on modern consumer GPUs: TinyLLaMa [^6^] Meant to run on consumer-grade GPUs: Mar 29, 2024 · LLaVA-1. We can run the LLMs locally and then use the API to integrate them with any application, such as an AI coding assistant on VSCode. The first runs into memory issues, the second, loaded with llama. H2O LLM Studio: Sep 14, 2024 · 2. In that case, you would need uncensored LLMs that you can run locally on The Common Admission Test (CAT) is a computer based test (CBT) for admission in a graduate management program. It’s expected to spark another wave of local LLMs that are fine-tuned based on it. Now, I can use LMStudio to run both the standard version and the coder version of Qwen2. e. It supports Dec 18, 2023 · The following outlines how a non-technical person can run an open-source LLM like Llama2 or Mistral locally on their Windows machine (the same instructions will also work on Mac or Linux, though Jan 30, 2025 · Best Ways to Run LLM on Mac: Conclusion In 2025, Mac users have multiple robust options for running LLMs locally, thanks to advancements in Apple Silicon and dedicated AI software. Before you choose the best LLM for your use case, you can take a closer look at the datasets it was tested on here. A lot of people here don't have a way to run flan 4bit models, so we don't know how well the models work. 5 lightweight LLMs you can run on low-power hardware. But which is the best LLM for coding? How can we decide which one to use? But you can also use it locally. cpp (which it seems to be configured on) loads, but is excruciatingly slow (like 0. Jul 19, 2024 · Running LLM on CPU-based system. So that puts limits for running things in memory and lack the dedicated GPU puts limits on faster replies on smaller modules. 2 with this example code on my modest 16GB Macbook Air M2, although I replaced CUDA with MPS as my GPU device. Jan 30, 2024 · Yes, you can run some smaller LLM models even on a 8GB VRAM system, and as a matter of fact I did that exact thing in this guide on running LLM models for local AI assistant roleplay chats, reaching speeds for up to around 20 tokens per second with small context window on my old trusted NVIDIA GeForce RTX 2070 SUPER (~short 2-3 sentence message Feb 22, 2025 · Quick Setup: Minimal fuss — download, install, and dive into local inference. If you’re looking for the best LLM for local use, this guide explores various models, their capabilities, hardware requirements, and factors to consider when choosing an LLM for your local machine. Apr 30, 2025 · Ollama is a tool used to run the open-weights large language models locally. What is a Local LLM? A Local LLM is a machine learning model deployed and executed on local hardware, rather than relying on external cloud services. Node. You can run 13B models with 16 GB RAM but they will be slow because of CPU inference. 0) aren't very useful compared to chatGPT, and the ones that are actually good (LLaMa 2 70B parameters) require way too much RAM for the average device. This approach isn So I would say the "best" model is entirely dependant on what you can actually run. 1. Its robust privacy measures and intuitive features make it an excellent choice for personal conversations. I want it to be able to run smooth enough on my computer but actually be good as well. For now I see following methods: ollama lmstudio python/golang code Can you recommend any other projects which help running LLM models locally? Thanks in advance! If you run offloaded partially to the CPU your performance is essentially the same whether you run a Tesla P40 or a RTX 4090 since you will be bottlenecked by your CPU memory speed. By using CPU and memory, local-llm makes LLM development more accessible to a broader audience. It was written in c/c++ and this means that it can be compiled to run on many platforms with cross compilation. May 21, 2024 · "If I have a big pile of PDFs and wanted to get an LLM to be really good at answering questions about what's in all those PDFs, would it be best for me to try running this locally?" So what if you used a paid LLM to analyze these PDFs and create the data, but then moved that data to a weaker LLM in order to run question-answer sessions on it? LLM inference on my M1 Max makes it heat up like playing the Sims did 10 years ago. 5-7b-q4. You can choose from a wide range of open-source models, tailor them to your specific tasks, and even experiment with different configurations to optimize performance. 0 locally, users will need access to high-end consumer hardware with powerful GPUs or multi-GPU setups. Command R+ has replaced Mixtral as my daily driver. It’s the only thing I do that turns the fans on. This knowledge will be invaluable when users are financially and technically capable of upgrading to and running larger modules while understanding their limitations. I want to run an LLM locally, the smartest possible one, not necessarily getting an immediate answer but achieving a speed of 5-10 tokens per second. Hi! That's super slow! I have rechecked for you and it is still as fast as I last posted. While it still can’t match Apple’s unified memory advantage for massive models, its RTX 5090 and high-speed RAM make it a powerful option for enthusiasts looking to push beyond 13B models without stepping up Mar 30, 2025 · 16 Tools to Run LLMs Locally 1. 3,432: 332: 62: 9: 30: MIT License: 4 days, 2 hrs, 7 mins: 40: LLamaSharp: A C#/. LM Studio: Your Local LLM Powerhouse. Local LLMs on CPU-only devices offer privacy (no data leaves your PC) and zero subscription fees. That expensive macbook your running at 64b could run q8s of all the 34b coding models, including deepseek 33b, codebooga (codellama-34b base) and phind-codellama-34b-v2. Oct 9, 2024 · LLaMa. Key Features: Offline Operation: Ensures all data processing remains local, safeguarding sensitive information. Mar 30, 2025 · Overall, the Lenovo Legion Pro 7i offers high performance-per-dollar and is one of the best non-Apple laptops for local LLM inference. However, there are times when one wants to explore the uncharted territory. Hopefully this quick guide can help people figure out what's good now because of how damn fast local llms move, and finetuners figure what models might be good to try training on. I’m pleasantly surprised by how well local LLMs perform even on older hardware with limited resources. If your question is what model is best for running ON a RTX 4090 and getting its full benefits then nothing is better than Llama 8B Instruct right now. 3. Oct 7, 2024 · Some Warnings About Running LLMs Locally. Developers benefit from local LLMs by maintaining control over data and working without internet dependency. Thanks! Share Add a Comment. You could perhaps run a very low bit Mixtral quant. For example, my 6gb vram gpu can barely manage to fit the 6b/7b LLM models when using the 4bit versions. In this article, I’ll share my hands-on […] As they are more limited than some bigger options given that they normally only support 2 memory slots. Kinda sorta. I've learnt loads from this community about running open-weight LLMs locally, and I understand how overwhelming it can be to navigate this landscape of open-source LLM inference tools. ContentsWavecoder-ultra-6. As far as i can tell it would be able to run the biggest open source models currently available. Comes pre-packaged with Ollama, a local LLM server that manages the language model for you. . Apr 17, 2024 · Related: 3 Open Source LLM With Longest Context Length. 40 for macOS on Apple silicon, Model Runner makes it easy to pull, run, and experiment with LLMs on your local machine As of its February launch, Chat with RTX can use either a Mistral or Llama 2 LLM running locally. With tools like Ollama and LM Studio, it’s never been easier to run powerful code-focused LLMs right from your laptop or workstation. Key features: All your data stays on your computer and is never sent to the cloud. The 34b range is where all the best coders are at, though I have noticed that Deepseek 67b is pretty good at it as well. GetStream blog listing the best tools for local LLM execution, with detailed insights. llama, the MLC project, and MPT-30B. But I thought it would be cool to provide GPT4 like features - chat, photo understanding, image generation, whisper and an easy-to-use simple UI all in one, and for free (or a very low price). This would traditionally prevent the application from taking advantage of GPU acceleration. Jun 9, 2024 · Local-llm. Apr 26, 2025 · Conclusion: The Future of AI is Local. Compare features, strengths, and weaknesses of AnythingLLM, GPT4All, Ollama, LM Studio, Jan, and more. AI – “Build AI apps with On-Device Models & Run locally on any device. 5-7B-ChatDeepseek CoderWizardCoder-Python-34B-V1. You can run Mistral 7B (or any variant) Q4_K_M with about 75% of layers offloaded to GPU, or you can run Q3_K_S with all layers offloaded to GPU. The test consists of three sections: Verbal Ability and Reading Comprehension (VARC), Data Interpretation and Logical Reasoning (DILR) and Quantitative Ability (QA). what are you "doing with LLM's" in your job that you want to run on a laptop? Hi, There are already quite a few apps running large models on mobile phones, such as LLMFarm, Private LLM, DrawThings, and etc. Now that we understand why LLMs need specialized hardware, let’s look at the specific hardware components required to run these models efficiently. Large Language Models (LLMs) are no longer just a niche; they’ve become the cornerstone of modern machine learning, representing the pinnacle of AI advancements. Its compatibility guess feature ensures that users download models suited to their hardware, preventing wasted time and resources. Run AI offline, ensure data privacy & achieve near-zero latency responses. After you select the preferred LLM, you can use different tools to run it locally. I am looking for a good local LLM that I can use for coding, and just normal conversations. Apr 25, 2025 · Most users access these models through cloud-based APIs, but interest is rapidly growing in running these LLM models locally—whether on a personal computer or server. Quantization This process converts the model’s weights from higher precision (e. Whether you’re a researcher, developer, or AI enthusiast, this guide will help you set up and deploy an LLM on your local machine efficiently. Once it's running, launch SillyTavern, and you'll be right where you left off. js or Python). This was originally written so that Facebooks Llama could be run on laptops with 4-bit quantization. However I get out of memory errors with just the CPU or using You might use the serverless or spot instance functionality Runpod has and figure out the smallest pod / LLM that works for your use. Ollama. Nov 15, 2024 · The 6 Best LLM Tools To Run Models Locally. It offers enhanced performance for various NLP tasks. Oct 15, 2024 · Best For: Users who need to run models on constrained devices or across different operating systems (Windows, macOS, Linux, mobile). It’s going to be a long time before running a local LLM will produce the type of results that you can get from querying ChatGPT or The LlamaEdge project makes it easy for you to run LLM inference apps and create OpenAI-compatible API services for open-source LLMs locally. Key Features of LLaMa. LM Studio. cpp. You can read my write up on LM Studio here: Local LLM Model in Private AI server in WSL. A fast inference library for running LLMs locally on modern consumer-class GPUs: 4,167: 312: 140: 53: 40: MIT License: 2 days, 3 hrs, 51 mins: 39: pocketpal-ai: An app that brings language models directly to your phone. 5, which has 32 billion parameters. A lot of discussions which model is the best, but I keep asking myself, why would average person need expensive setup to run LLM locally when you can get ChatGPT 3. Jun 17, 2024 · No. Dec 31, 2024 · It's the best Polish-language model that I was able to run locally. Jan 28, 2025 · There are several benchmarks that compare LLMs performance with various datasets and tasks, but I recommend the HuggingFace LLM Leaderboard. Hardware Requirements: To deploy SOLAR-10. I’m starting to write my own python code for integrating with my local run models. I'd stick to 3B and 7B if you want speed. The thermal bottleneck on an Air is going to be real. Contact me if you think some other model should be on the list. By default, Ollama uses 4-bit quantization. Why Run an LLM Locally? Aug 27, 2024 · Learn how to run and test LLMs like DeepSeek R1 offline using GUI-based tools like LM Studio or the command line with Ollama. Now available in Beta with Docker Desktop 4. Of course you can go for multiple GPUs and run bigger quants of llama 3 70B too. But I know little to no python, and I am on a Windows 11 box. May 1, 2025 · Learn how to run large language models (LLMs) on your own device with these tools that offer privacy, offline access, and customization. Whether the interest is in privacy, experimentation, or offline capabilities, this guide covers everything needed to set up LLMs locally—especially if you are just getting Mar 3, 2025 · Master local LLM deployment: Compare DeepSeek, Llama 3. I want something that can assist with: - text writing - coding in py, js, php Jan 17, 2025 · Ollama is an open-source tool that runs large language models (LLMs) directly on a local machine. In addition I’ve text-generation-webui setup, with nice speech-to-text and text-to-speech locally. Compare the features, benefits, and requirements of the top six local LLM tools for developers. 07t/sec). Run Llama, Gemma 3, DeepSeek locally on your computer. You'd probably do the microphone and triggerword stuff on your Pi and have it connect to the runpod server to run the TTS/STT and LLM bits. hpfyqat nxivzj ugtvnb zui qwerxo qcrejf aqsq axut rpwgg omntzh