正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

LM Studio is the most popular way to run open-source LLMs on your own hardware. Your Hermes Agent now runs natively on LM Studio: auto-discovering your models, loading them on demand with the right context size, and using the right reasoning level for each model.

Nous Research

238,129 subscribers

186,036 次观看 • 2 个月前 •via X (Twitter)

教育科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Create your own local and free AI agent using an open source model You can combine: - IBM's Granite 3.3 8B AI model - LM Studio to run it on a laptop - Smolagents to build your agent Small AI models are now powerful enough to run an autonomous agent. Thanks to IBM France for sponsoring this content!

Create your own local and free AI agent using an open source model You can combine: - IBM's Granite 3.3 8B AI model - LM Studio to run it on a laptop - Smolagents to build your agent Small AI models are now powerful enough to run an autonomous agent. Thanks to IBM France for sponsoring this content!

Paul Couvert

18,890 次观看 • 1 年前

local LLMs on Mac are getting good. but the workflow around models is still messy. you have models in: •⁠ ⁠LM Studio •⁠ ⁠Ollama •⁠ ⁠Hugging Face cache •⁠ ⁠random folders •⁠ ⁠manual downloads and every runtime expects something slightly different. we built ModelHub to clean up this layer. it’s a native macOS menu bar app for discovering, downloading, and managing local LLMs. not a replacement for Ollama, oMLX or LM Studio. it sits beside them. Ollama = run models MLX = Apple Silicon acceleration LM Studio = local model workspace Hugging Face = model ecosystem ModelHub = model discovery + management layer we’re live on Product Hunt today. would love feedback from people running local models on Mac.

local LLMs on Mac are getting good. but the workflow around models is still messy. you have models in: •⁠ ⁠LM Studio •⁠ ⁠Ollama •⁠ ⁠Hugging Face cache •⁠ ⁠random folders •⁠ ⁠manual downloads and every runtime expects something slightly different. we built ModelHub to clean up this layer. it’s a native macOS menu bar app for discovering, downloading, and managing local LLMs. not a replacement for Ollama, oMLX or LM Studio. it sits beside them. Ollama = run models MLX = Apple Silicon acceleration LM Studio = local model workspace Hugging Face = model ecosystem ModelHub = model discovery + management layer we’re live on Product Hunt today. would love feedback from people running local models on Mac.

sabesh 📟

31,497 次观看 • 2 个月前

You can run a free and open-source alternative to Claude Code locally on your laptop! - Local AI model w/ Qwen3 Coder - Runs on your machine w/ LM Studio - Open-source VS Code extension w/ Cline Completely private (offline) and unlimited Setup and how it works: 00:00 Intro 01:11 LM Studio 02:10 Local AI model 03:38 Load the model 05:09 Start the server 05:33 Setup Cline 07:20 Prompt & example 09:02 Developer logs 10:12 Result reveal

You can run a free and open-source alternative to Claude Code locally on your laptop! - Local AI model w/ Qwen3 Coder - Runs on your machine w/ LM Studio - Open-source VS Code extension w/ Cline Completely private (offline) and unlimited Setup and how it works: 00:00 Intro 01:11 LM Studio 02:10 Local AI model 03:38 Load the model 05:09 Start the server 05:33 Setup Cline 07:20 Prompt & example 09:02 Developer logs 10:12 Result reveal

Paul Couvert

72,498 次观看 • 9 个月前

Holy shit! Did we just open-source the smallest video-LM in the world? SmolVLM2 is runnning natively on your iPhone 🚀

Holy shit! Did we just open-source the smallest video-LM in the world? SmolVLM2 is runnning natively on your iPhone 🚀

Miquel Farré

71,512 次观看 • 1 年前

Private AI browser with the OpenClaw agent on free local models Run your agent on Qwen, Gemma, or Nemotron directly in the browser Open source. Private. Runs on your local device

Private AI browser with the OpenClaw agent on free local models Run your agent on Qwen, Gemma, or Nemotron directly in the browser Open source. Private. Runs on your local device

Sigma Browser

114,882 次观看 • 2 个月前

ComfyUI is the most flexible, composable, and powerful open-source media generation tool with a massive ecosystem of workflows and custom nodes. Your Hermes Agent can now install, launch, manage, and run sophisticated ComfyUI workflows on demand.

ComfyUI is the most flexible, composable, and powerful open-source media generation tool with a massive ecosystem of workflows and custom nodes. Your Hermes Agent can now install, launch, manage, and run sophisticated ComfyUI workflows on demand.

Nous Research

604,381 次观看 • 2 个月前

A 10B Chinese model beats models 20x its size. And it runs on your laptop. Step 3 VL10B uses parallel reasoning to think like 16 experts at once. → Beats 200B parameter models → Scores 92.2% on multimodal benchmarks → Runs 16 reasoning paths simultaneously → Open source on Hugging Face → Works offline on your hardware OCR. GUI understanding. STEM problems. All covered. Completely free to download. Want the technical breakdown? DM me.

A 10B Chinese model beats models 20x its size. And it runs on your laptop. Step 3 VL10B uses parallel reasoning to think like 16 experts at once. → Beats 200B parameter models → Scores 92.2% on multimodal benchmarks → Runs 16 reasoning paths simultaneously → Open source on Hugging Face → Works offline on your hardware OCR. GUI understanding. STEM problems. All covered. Completely free to download. Want the technical breakdown? DM me.

Julian Goldie SEO

37,165 次观看 • 6 个月前

DeepSeek released R1, the best open-source reasoning model that is on par with OpenAI's o1! I have built a RAG app to chat with your PDF files using the DeepSeek R1 model, running locally on your computer. 100% Open Source

DeepSeek released R1, the best open-source reasoning model that is on par with OpenAI's o1! I have built a RAG app to chat with your PDF files using the DeepSeek R1 model, running locally on your computer. 100% Open Source

Sumanth

678,638 次观看 • 1 年前

Andrej Karpathy (co-founder of OpenAI, Eureka Labs): "The future of AI is not all in the cloud. The most important models will run locally on your hardware under your control." June 2026 is the first time that the future is actually accessible to everyone! Here is what the local LLM landscape looks like right now: → raspberry pi 5: coherent chatbot, no GPU required → macbook air: matches GPT-3.5 quality on most tasks natively → used RTX 3090 at $700: something close to GPT-4 running locally → ollama: one command to an openAI-compatible endpoint, every major toolchain integrates with it → LM studio: best GUI, native MLX acceleration on apple silicon, MCP support in 0.4.0 → llama.cpp: the engine everything else runs on, 90MB footprint, runs on raspberry pi to android → the honest case: 80% of daily work is genuinely good enough locally right now Your prompts never leave your machine. no per-token billing. no rate limits. no refusals. The playbook for every hardware tier, from Raspberry Pi to RTX 5090, is here. Bookmark it so you do not lose it! Follow NeilXbt for more local AI and open source intelligence that tracks the hardware and tooling most people discover six months late.

Andrej Karpathy (co-founder of OpenAI, Eureka Labs): "The future of AI is not all in the cloud. The most important models will run locally on your hardware under your control." June 2026 is the first time that the future is actually accessible to everyone! Here is what the local LLM landscape looks like right now: → raspberry pi 5: coherent chatbot, no GPU required → macbook air: matches GPT-3.5 quality on most tasks natively → used RTX 3090 at $700: something close to GPT-4 running locally → ollama: one command to an openAI-compatible endpoint, every major toolchain integrates with it → LM studio: best GUI, native MLX acceleration on apple silicon, MCP support in 0.4.0 → llama.cpp: the engine everything else runs on, 90MB footprint, runs on raspberry pi to android → the honest case: 80% of daily work is genuinely good enough locally right now Your prompts never leave your machine. no per-token billing. no rate limits. no refusals. The playbook for every hardware tier, from Raspberry Pi to RTX 5090, is here. Bookmark it so you do not lose it! Follow NeilXbt for more local AI and open source intelligence that tracks the hardware and tooling most people discover six months late.

NeilXbt

19,405 次观看 • 1 个月前

The new gpt-oss-120b from OpenAI is now the best general purpose model to run on a Framework Desktop! ~40 tok/s on the MXFP4 version in LM Studio on Fedora 42.

The new gpt-oss-120b from OpenAI is now the best general purpose model to run on a Framework Desktop! ~40 tok/s on the MXFP4 version in LM Studio on Fedora 42.

Framework

129,716 次观看 • 11 个月前

Stop hardcoding one model name in your code. Now you can give each request a policy: a small rule for what the call needs It picks the right model for the job, on your own keys This is unhardcoded, our new open source routing for AI models, live today

Stop hardcoding one model name in your code. Now you can give each request a policy: a small rule for what the call needs It picks the right model for the job, on your own keys This is unhardcoded, our new open source routing for AI models, live today

GenLayer

92,385 次观看 • 1 个月前

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

Nidhi Singh

16,289 次观看 • 1 个月前

Here is a real-life run, end-to-end from training to using the trained LLM in LM Studio by LM Studio MLX-LoRA-Studio gives you a user friendly, extremely customisable training interface for fine-tuning and training LLMs. Its a MacOS native app, front- and backend. Will be releasing the App in the coming days. GH Repo:

Here is a real-life run, end-to-end from training to using the trained LLM in LM Studio by LM Studio MLX-LoRA-Studio gives you a user friendly, extremely customisable training interface for fine-tuning and training LLMs. Its a MacOS native app, front- and backend. Will be releasing the App in the coming days. GH Repo:

Gökdeniz Gülmez

11,780 次观看 • 1 个月前

Run Cline on Local AI models with Atomic Chat! Cline is a coding agent trusted by 8M+ developers. Write, refactor, ship code securely on your own hardware with local models powered by atomic.chat — no cloud, private, free and open-source

Run Cline on Local AI models with Atomic Chat! Cline is a coding agent trusted by 8M+ developers. Write, refactor, ship code securely on your own hardware with local models powered by atomic.chat — no cloud, private, free and open-source

atomic.chat

43,940 次观看 • 1 个月前

Sam Altman on Open Source AI's Future⁣ ⁣ "Right now, what everybody wants is just the most capable frontier coding model they can have. The big frontier models, even if we made them open source, are hard to run." — #sama

Sam Altman on Open Source AI's Future⁣ ⁣ "Right now, what everybody wants is just the most capable frontier coding model they can have. The big frontier models, even if we made them open source, are hard to run." — #sama

AI Insights

19,607 次观看 • 1 个月前

📢 New in Visual Studio: Bring Your Own Model to Chat We’re expanding flexibility in Copilot for Visual Studio. You can now connect API keys from providers like OpenAI, Anthropic, and Google to run Chat on the model of your choice. This update gives you: ✅ Choice – Access the latest models beyond the built-in defaults. ✅ Customization – Select models that fit your infrastructure and requirements. ✅ Control – Manage API usage, limits, and billing directly with your provider. ✅ Flexibility – Switch seamlessly between Copilot’s built-in models and your own. This release is the first step toward a more open and customizable chat experience in Visual Studio, with more providers and capabilities to come. 🔗

📢 New in Visual Studio: Bring Your Own Model to Chat We’re expanding flexibility in Copilot for Visual Studio. You can now connect API keys from providers like OpenAI, Anthropic, and Google to run Chat on the model of your choice. This update gives you: ✅ Choice – Access the latest models beyond the built-in defaults. ✅ Customization – Select models that fit your infrastructure and requirements. ✅ Control – Manage API usage, limits, and billing directly with your provider. ✅ Flexibility – Switch seamlessly between Copilot’s built-in models and your own. This release is the first step toward a more open and customizable chat experience in Visual Studio, with more providers and capabilities to come. 🔗

Visual Studio

11,873 次观看 • 11 个月前

Hermes Agent released v0.14, and it just made every other AI agent framework feel small. It now drives your computer. Searches X natively. Joins your Microsoft Teams calls. AND runs Grok with a 1M context window. (and for my crypto bro HyperLiquid) The AI agent era is crazy and beautiful.

Hermes Agent released v0.14, and it just made every other AI agent framework feel small. It now drives your computer. Searches X natively. Joins your Microsoft Teams calls. AND runs Grok with a 1M context window. (and for my crypto bro HyperLiquid) The AI agent era is crazy and beautiful.

Antoine Rousseaux

24,505 次观看 • 2 个月前

Mistral Vibe CLI running Devstral-small-2-2512 on M3 Ultra 512GB with LM Studio as backend 🔥 First part of the video 1x and the remaining 2x Great speed overall, 27 toks/s as average tracked on LM Studio console. Details to run it below 🧵

Mistral Vibe CLI running Devstral-small-2-2512 on M3 Ultra 512GB with LM Studio as backend 🔥 First part of the video 1x and the remaining 2x Great speed overall, 27 toks/s as average tracked on LM Studio console. Details to run it below 🧵

Ivan Fioravanti ᯅ

49,682 次观看 • 7 个月前

Just for fun, here's what 32 simultaneous long-context generations with Qwen3 Next 80B looks like on an M3 Ultra. Using the new batch generation in mlx-lm. Context size for each is about 5k tokens:

Just for fun, here's what 32 simultaneous long-context generations with Qwen3 Next 80B looks like on an M3 Ultra. Using the new batch generation in mlx-lm. Context size for each is about 5k tokens:

Awni Hannun

50,272 次观看 • 10 个月前