Apps for running AI locally
Every app that runs these models locally, plus the coding agents, assistants and reverse-engineering plugins that use them: what each opens, which systems and GPUs it supports, and our pick for your setup.
Run LLMs on your Desktop 21
Point-and-click apps, command-line tools and servers that download a model and run it on your own Mac, Windows or Linux computer. Which one to use.
Run LLMs on a mobile device 3
For phones, tablets, foldables and other devices that run iOS, iPadOS or Android. Small models (about 4B parameters and under with 8 GB of memory, up to 8B with 12 GB or more) run on the device itself, so chats stay private and work offline once the model is downloaded. Which models your device runs.
Run LLMs on a Raspberry Pi, Jetson or other board 8
Apps with a Linux ARM64 build. On a Raspberry Pi or Rockchip board they run small models (up to about 3B, or 8B on 8 GB and up) on the CPU; a Jetson runs them on its GPU with CUDA. The NPUs on these boards and add-on AI accelerators need their makers’ own tools. Which models your board runs.
Run LLMs on a NAS 3
Apps you can run on a NAS (network attached storage) itself, as a container (Docker) or from the NAS maker’s app store. Most NAS processors run small models (about 4B parameters and under) on the CPU, so the amount of memory (RAM) fitted sets what loads; a few models with a graphics card slot or a newer processor run larger ones. Each app’s page lists its container image. Which models your NAS runs · NAS models by maker.
Make images and video 13
Apps that make pictures and short clips on your own graphics card or Mac, from node editors like ComfyUI to one-window apps and a Krita plug-in. Image models · video models.
System One · decision models 16
Apps that run decision models: safety classifiers, rerankers, judges and zero-shot classifiers that answer with a label, score or probability. Which one to use.
Coding agents 14
Agents do the work: they read and edit your code and run commands. They do not run the AI model themselves. Each one talks to a model server such as Ollama, LM Studio or llama.cpp, so pointing one at a local model means no API bill and your code stays on your machine. Pick a model with tool calling.
Personal assistants 11
Assistants for notes, documents, chat and everyday tasks beyond code. Most connect to a local model server such as Ollama; AnythingLLM brings its own engine.
Reverse engineering 9
Plugins that bring a local model into the reverse-engineering tools you already use: Ghidra, IDA Pro, Binary Ninja, radare2 and JADX for Android apps. A local model keeps the binary, firmware or app you are studying off third-party servers. Some add a chat panel; the MCP ones let an agent drive the tool and need a model with tool calling. Models for reverse engineering.
Which app should you use?
Our first pick for common setups. The same rules run on every model page with your exact hardware. These picks are model-running apps; to edit code or run tasks with the model, add one of the coding agents, assistants or reverse-engineering plugins on top.
Step 1
Tell us your hardware first
The table below shows examples for common setups, not your own. To see which app we would pick for you, choose your computer.
Common setups
| Example computer | Small model that fits8B | Bigger than GPU memory70B | Serving a team32B |
|---|---|---|---|
| Mac with Apple silicon | LM Studio | LM Studio | LM Studio |
| Windows PC, NVIDIA GeForce | Ollama | LM Studio | Ollama |
| Windows PC, AMD Radeon | Lemonade | llama.cpp | Lemonade |
| Windows PC, Intel Arc | llama.cpp | llama.cpp | llama.cpp |
| Ryzen AI mini PC or laptop | Lemonade | Lemonade | Lemonade |
| Linux, NVIDIA GeForce | Ollama | LM Studio | Ollama |
| Linux server, datacenter GPUs | vLLM | vLLM | vLLM |
| NVIDIA Jetson board | Ollama | LM Studio | Ollama |
| Raspberry Pi or ARM board | Ollama | LM Studio | Ollama |
Which app for decision models?
Scorers that read the input once (rerankers, classifiers, reward models) belong in a scoring server or a Python library; guard and judge models that write a short answer run in the same apps as LLMs. Agents are not listed here: they call a model server and do not run decision models themselves.
Step 1
Tell us your hardware first
The table below shows examples for common setups, not your own. To see which app we would pick for your decision models, choose your computer.
Common setups
| Example computer | Safety checkQwen3Guard 4B | RerankerBGE Reranker v2 M3 | Zero-shot classifierDeBERTa | Reward judgeSkywork 8B | Label decisionsGLiNER2.5 Decide |
|---|---|---|---|---|---|
| Mac with Apple silicon | LM Studio | llama.cpp | Infinity | Sentence Transformers | GLiNER |
| Windows PC, NVIDIA GeForce | LM Studio | llama.cpp | Sentence Transformers | Sentence Transformers | GLiNER |
| Windows PC, AMD Radeon | Lemonade | llama.cpp | Sentence Transformers | Sentence Transformers | GLiNER |
| Windows PC, Intel Arc | llama.cpp | llama.cpp | Sentence Transformers | vLLM | GLiNER |
| Linux, NVIDIA GeForce | LM Studio | llama.cpp | Infinity | vLLM | GLiNER |
| Linux server, datacenter GPUs | vLLM | llama.cpp | Infinity | vLLM | GLiNER |
| NVIDIA Jetson board | vLLM | llama.cpp | Infinity | vLLM | GLiNER |
| Raspberry Pi or ARM board | LM Studio | llama.cpp | Infinity | Sentence Transformers | GLiNER |
System One models answer with a label, a score or a probability that code can use directly, instead of writing text. They are the fast, focused judgments behind safety filters, search ranking, answer grading and routing. Chat LLMs do the opposite job: slower, open-ended reasoning and writing.
Compare every app
75 apps: 41 that run models and 34 agents and assistants that use them. Filter by type, operating system, GPU or file format from the column headers. Agents show “Via server” for GPUs because they use whatever your model server runs on.
Step 1
Tell us your hardware first
The table below shows examples for common setups, not your own. To see which of these apps work on your computer, choose it.
| App | Type | Runs | Systems | GPUs | Formats | Engine | Models | Stars | License |
|---|---|---|---|---|---|---|---|---|---|
| LM Studio | Desktop app | LLMs, Decisions | macOSWindowsLinuxLinux on ARM boards | Apple, MLX, NVIDIA, Vulkan, AMD, CPU | GGUF, MLX | llama.cpp, MLX | 604 | 5,412 | Free, closed |
| Ollama | CLI + API | LLMs, Decisions | macOSWindowsLinuxLinux on ARM boards | Apple, MLX, NVIDIA, AMD, Vulkan, CPU | GGUF | llama.cpp, MLX | 590 | 186,373 | Open source |
| llama.cpp | CLI + API | LLMs, Decisions | macOSWindowsLinuxLinux on ARM boards | Apple, NVIDIA, AMD, Vulkan, Intel, CPU | GGUF | llama.cpp | 593 | 133,757 | Open source |
| Jan | Desktop app | LLMs, Decisions | macOSWindowsLinux | Apple, NVIDIA, Vulkan, CPU, MLX | GGUF | llama.cpp, MLX | 604 | 45,605 | Open source |
| MLX LM | CLI + API | LLMs, Decisions | macOS | MLX | MLX | MLX | 417 | 7,595 | Open source |
| vLLM | Server | LLMs, Decisions | WSLWindowsLinuxLinux on ARM boards | NVIDIA, AMD, Intel | Safetensors, AWQ, GPTQ, FP8 | vLLM | 665 | 96,557 | Open source |
| SGLang | Server | LLMs, Decisions | WSLWindowsLinuxLinux on ARM boards | NVIDIA, AMD | Safetensors, AWQ, GPTQ, FP8 | SGLang | 655 | 38,584 | Open source |
| Docker Model Runner | CLI + API | LLMs, Decisions | macOSWindowsLinuxLinux on ARM boards | Apple, NVIDIA, AMD, Vulkan, CPU | GGUF, Safetensors | llama.cpp, vLLM | 648 | 659 | Open source |
| Lemonade | Desktop app | LLMs, Decisions | macOSWindowsLinux | Vulkan, AMD, NPU, Apple, CPU | GGUF, ONNX | llama.cpp, ONNX Runtime GenAI | 593 | 6,147 | Open source |
| Unsloth Desktop | Desktop app | LLMs, Images, Decisions | macOSWindowsLinux | NVIDIA, AMD, Intel, Apple, MLX, CPU | GGUF, MLX | llama.cpp, MLX, stable-diffusion.cpp | 630 | 79,201 | Open source |
| Atomic Chat | Desktop app | LLMs, Decisions | macOSWindowsLinux | Apple, MLX, NVIDIA, Vulkan, CPU | GGUF, MLX | llama.cpp, MLX-VLM | 604 | 1,961 | Open source |
| Pi | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 120,829 | Open source |
| Hermes Agent | Assistant | LLMs | macOSWSLWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 261,739 | Open source |
| OpenClaw | Assistant | LLMs | macOSWSLWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 394,214 | Open source |
| OpenCode | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 225,512 | Open source |
| Codex CLI | Coding agent | LLMs | macOSWSLWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 133,798 | Open source |
| OpenHands | Coding agent | LLMs | macOSWSLWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 92,970 | Open source |
| Zed | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 94,469 | Open source |
| Cline | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 71,473 | Open source |
| Open Interpreter | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 68,841 | Open source |
| Goose | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 56,371 | Open source |
| Aider | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 50,026 | Open source |
| Tabby | Coding agent | LLMs | macOSWSLWindowsLinux | Own engine | GGUF, MLX | runs its own models | — | 33,925 | Open source |
| Crush | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 29,004 | Source-available |
| Qwen Code | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 29,105 | Open source |
| Kilo Code | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 27,909 | Open source |
| Open WebUI | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 158,130 | Source-available |
| AnythingLLM | Assistant | LLMs | macOSWindowsLinux | Own engine | GGUF, MLX | built-in engine | — | 68,067 | Open source |
| Khoj | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 38,069 | Open source |
| Letta | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 25,388 | Open source |
| ComfyUI | Desktop app | Images, Video | macOSWindowsLinuxLinux on ARM boards | NVIDIA, AMD, Intel, Apple, CPU | Safetensors, GGUF | PyTorch, GGUF via ComfyUI-GGUF | 100 | 145,785 | Open source |
| Draw Things | Desktop app | Images, Video | macOSiOS | Apple | Safetensors, Draw Things format | Draw Things | 52 | 614 | Free, closed |
| DiffusionBee | Desktop app | Images | macOS | Apple | Safetensors | DiffusionBee | 14 | 13,589 | Open source |
| JoyFusion | Desktop app | Images | macOS | Core ML | Core ML | Core ML | 4 | — | Free, closed |
| Text Embeddings Inference | Server | Decisions | macOSWSLWindowsLinux | NVIDIA, Apple, CPU | Safetensors | TEI | 6 | 5,113 | Open source |
| Infinity | Server | Decisions | macOSWSLWindowsLinuxLinux on ARM boards | NVIDIA, AMD, Apple, CPU | Safetensors, ONNX | PyTorch, ONNX, CTranslate2 | 12 | 2,984 | Open source |
| LocalAI | Server | Decisions | macOSWSLWindowsLinuxLinux on ARM boards | NVIDIA, AMD, Intel, Vulkan, Apple, CPU | GGUF, Safetensors | llama.cpp, rerankers, Transformers | 30 | 50,258 | Open source |
| Sentence Transformers | Library | Decisions | macOSWindowsLinuxLinux on ARM boards | NVIDIA, AMD, Apple, CPU | Safetensors, ONNX | PyTorch | 64 | 19,266 | Open source |
| GLiNER | Library | Decisions | macOSWindowsLinuxLinux on ARM boards | NVIDIA, Apple, CPU | Safetensors, ONNX | PyTorch, ONNX | 6 | 4,236 | Open source |
| GhidrAssist | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 14 | 779 | Open source |
| ReVa | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 5 | 952 | Open source |
| GhidraMCP | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 5 | 11,844 | Open source |
| OGhidra | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 5 | 466 | Open source |
| Gepetto | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 14 | 3,485 | Open source |
| IDA Pro MCP | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 5 | 13,413 | Open source |
| BinAssist | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 14 | 68 | Open source |
| r2ai and decai | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 14 | 536 | Open source |
| JADX AI MCP | RE plugin | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 5 | 2,996 | Open source |
| GPT4All | Desktop app | LLMs | macOSWindowsLinux | Vulkan, NVIDIA, Apple, CPU | GGUF | llama.cpp | 287 | 77,347 | Open source |
| KoboldCpp | Desktop app | LLMs | macOSWindowsLinux | NVIDIA, Vulkan, Apple, CPU | GGUF | llama.cpp | 560 | 12,194 | Open source |
| Text Generation WebUI | Desktop app | LLMs | macOSWindowsLinux | NVIDIA, AMD, Vulkan, Apple, CPU | GGUF, Safetensors | llama.cpp, Transformers, ExLlamaV3 | 619 | 47,734 | Open source |
| llamafile | CLI + API | LLMs | macOSWindowsLinuxLinux on ARM boards | NVIDIA, Apple, CPU | GGUF | llama.cpp | 560 | 26,588 | Open source |
| Msty Studio | Desktop app | LLMs | macOSWindowsLinux | Apple, MLX, NVIDIA, AMD, CPU | GGUF, MLX | Ollama, llama.cpp, MLX | 579 | — | Free, closed |
| Llama (macOS) | Desktop app | LLMs | macOS | Apple | GGUF | llama.cpp | 560 | 1,752 | Open source |
| RecurseChat | Desktop app | LLMs | macOS | Apple | GGUF | llama.cpp | 560 | — | Free, closed |
| Inferencer | Desktop app | LLMs | macOS | MLX | MLX | MLX | 413 | — | Free, closed |
| node-llama-cpp | Library | LLMs | macOSWindowsLinuxLinux on ARM boards | Apple, NVIDIA, Vulkan, CPU | GGUF | llama.cpp | 560 | 2,200 | Open source |
| exo | Server | LLMs | macOSLinux | MLX, CPU | MLX | MLX | 413 | 48,251 | Open source |
| Invoke | Desktop app | Images | macOSWindowsLinux | NVIDIA, AMD, Apple, CPU | Safetensors, GGUF | PyTorch | 29 | 29,023 | Open source |
| SwarmUI | Desktop app | Images, Video | macOSWindowsLinux | NVIDIA, AMD, Intel, Apple, CPU | Safetensors, GGUF | ComfyUI | 100 | 4,752 | Open source |
| Forge Neo | Desktop app | Images | WindowsLinux | NVIDIA, AMD | Safetensors, GGUF | PyTorch | 30 | 1,891 | Open source |
| Fooocus | Desktop app | Images | macOSWindowsLinux | NVIDIA, AMD, Apple, CPU | Safetensors | PyTorch | 9 | 53,844 | Open source |
| SD.Next | Desktop app | Images, Video | macOSWindowsLinux | NVIDIA, AMD, Intel, Apple, CPU | Safetensors, GGUF | PyTorch | 100 | 7,373 | Open source |
| Stability Matrix | Desktop app | Images, Video | macOSWindowsLinux | NVIDIA, AMD, Intel, Apple, CPU | Safetensors, GGUF | installs ComfyUI, Forge, InvokeAI, SwarmUI, SD.Next or Fooocus | 100 | 8,971 | Open source |
| Krita AI Diffusion | Desktop app | Images | macOSWindowsLinux | NVIDIA, AMD, Apple, CPU | Safetensors, GGUF | ComfyUI | 21 | 10,816 | Open source |
| WanGP | Desktop app | Video | WindowsLinux | NVIDIA, AMD | Safetensors | PyTorch | 21 | 11,277 | Open source |
| Continue | Coding agent | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 36,385 | Open source |
| SillyTavern | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 35,163 | Open source |
| LibreChat | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 46,585 | Open source |
| Cherry Studio | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 53,134 | Open source |
| Chatbox | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 42,211 | Open source |
| PrivateGPT | Assistant | LLMs | macOSWindowsLinux | Via server | GGUF, MLX | Your model server | 238 | 57,624 | Open source |
| PocketPal AI | Mobile app | LLMs | iOSAndroid | Apple, OpenCL, CPU | GGUF | llama.cpp | 560 | 8,952 | Open source |
| ChatterUI | Mobile app | LLMs | Android | CPU | GGUF | llama.cpp | 560 | 2,865 | Open source |
| LLM Farm | Mobile app | LLMs | iOS | Apple, CPU | GGUF | llama.cpp | 560 | 2,079 | Open source |
How we choose an app
- The files that exist for the model. GGUF opens in llama.cpp, Ollama, LM Studio, Jan, Lemonade, Docker, KoboldCpp, llamafile, Msty and others; MLX opens in LM Studio, MLX LM, Inferencer and others on Apple silicon; the original safetensors weights need vLLM, SGLang or Text Generation WebUI. We check Hugging Face and Ollama for every model, the same signals Hugging Face uses for its “Use this model” menu.
- Your operating system and GPU. MLX is Mac-only; vLLM and SGLang are Linux (Windows through WSL2); Lemonade is built for AMD Radeon and Ryzen AI; llama.cpp has the broadest GPU support (CUDA, ROCm, Vulkan, SYCL, Metal).
- Whether the model fits. If part of it has to sit in system RAM, only llama.cpp-based apps can split it; vLLM, SGLang and MLX need it all in GPU or unified memory.
- Published speed tests. On an M4 Max, MLX generated 21–87% faster than llama.cpp for 4-bit models up to 8B and tied around 27B; llama.cpp still prefills long prompts faster. On an RTX 4090, vLLM (54 tok/s) and llama.cpp (50 tok/s) were close for one user, Ollama’s draft decoding reached 76 tok/s, and with spare memory vLLM handled 32 users far better.
- Decision models. Guard and judge models that write a short answer follow the LLM rules above. Rerankers, classifiers and reward models only score their input, so they go to a scoring server (Text Embeddings Inference for BERT, XLM-RoBERTa and ModernBERT models; Infinity for DeBERTa; vLLM or SGLang with big GPUs), to llama.cpp when a GGUF build exists, or to a few lines of Python. GLiNER-family models need the GLiNER libraries. Ollama has no rerank endpoint, so it only runs the guard and judge models.
- Agents, assistants and plugins. Coding agents, personal assistants, reverse-engineering plugins and chat front ends are not ranked against the apps above, because they do not run a model: they send requests to one. We list them by GitHub stars and show which need a model server and which, like Tabby and AnythingLLM, bring their own. GPT4All only gets models released up to mid-2025, because its engine has not been updated since. For a local model to work as an agent it must support tool calling.
- Ease and popularity. Point-and-click apps rank above command-line tools for one person; GitHub stars and maintenance break ties.
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.