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Dexter can now use local LLMs. We finally added ollama support today. Includes models like: • qwen 3 • gemma 3 • deepseek r1 Because Dexter is built on LangChain, switching between local and cloud models is easy. Huge thanks to Harsh Gupta for shipping this.

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virat

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36,456 görüntüleme • 6 ay önce •via X (Twitter)

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I’ve been building Dexter for 2 months now. It’s like Claude Code, but for finance. What Dexter can do: • find undervalued stocks • analyze them in detail • build investment thesis All of the code is open source. Bonus: Dexter can also run on local LLMs.
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I’ve been building Dexter for 2 months now. It’s like Claude Code, but for finance. What Dexter can do: • find undervalued stocks • analyze them in detail • build investment thesis All of the code is open source. Bonus: Dexter can also run on local LLMs.

Virat Singh

553,077 görüntüleme • 6 ay önce

Ollama can now think! 🤔🤔🤔 For thinking models, and especially useful for very thoughtful models like DeepSeek-R1-0528, Ollama can separate the thoughts and the response. Thinking can also be disabled! This is useful for getting a direct response. This works across Ollama's CLI, API, and Python/JavaScript libraries. 🧵 blog post 👇👇👇
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Ollama can now think! 🤔🤔🤔 For thinking models, and especially useful for very thoughtful models like DeepSeek-R1-0528, Ollama can separate the thoughts and the response. Thinking can also be disabled! This is useful for getting a direct response. This works across Ollama's CLI, API, and Python/JavaScript libraries. 🧵 blog post 👇👇👇

ollama

106,267 görüntüleme • 1 yıl önce

I added ollama to our AI hedge fund. We can now run the system 100% for free. The AI hedge fund will: 1 • install ollama 2 • download LLMs 3 • run the trading system You can still use agents like Warren Buffett, etc. as before. Ollama was a very popular ask. I am pumped this is finally live!
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I added ollama to our AI hedge fund. We can now run the system 100% for free. The AI hedge fund will: 1 • install ollama 2 • download LLMs 3 • run the trading system You can still use agents like Warren Buffett, etc. as before. Ollama was a very popular ask. I am pumped this is finally live!

virat

32,142 görüntüleme • 1 yıl önce

Check this!! A 100% open-source toolkit to work with LLMs. Transformer Lab is an app to experiment with LLMs: - Train, fine-tune, or chat. - One-click LLM download (DeepSeek, Gemma, etc.) - Drag-n-drop UI for RAG. - Built-in logging, and more. 100% local!
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Check this!! A 100% open-source toolkit to work with LLMs. Transformer Lab is an app to experiment with LLMs: - Train, fine-tune, or chat. - One-click LLM download (DeepSeek, Gemma, etc.) - Drag-n-drop UI for RAG. - Built-in logging, and more. 100% local!

Avi Chawla

74,926 görüntüleme • 1 yıl önce

DeepSeek R1 is *the* best model available right now. It's at the level of o1, but you can use it for free, and it's much faster. A huge leap forward that nobody saw coming. No wonder so many people are throwing tantrums online trying to discredit the Chinese students who built this. You can use DeepSeek in Visual Studio Code right now: 1. Install the Qodo Gen AI extension 2. Select DeepSeek R1 from their list of models The Qodo team is hosting DeepSeek on their servers, so none of your data will go to China. I've been building a Tetris game using DeepSeek, and this is the most impressive model I've seen so far.
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DeepSeek R1 is *the* best model available right now. It's at the level of o1, but you can use it for free, and it's much faster. A huge leap forward that nobody saw coming. No wonder so many people are throwing tantrums online trying to discredit the Chinese students who built this. You can use DeepSeek in Visual Studio Code right now: 1. Install the Qodo Gen AI extension 2. Select DeepSeek R1 from their list of models The Qodo team is hosting DeepSeek on their servers, so none of your data will go to China. I've been building a Tetris game using DeepSeek, and this is the most impressive model I've seen so far.

Santiago

1,224,059 görüntüleme • 1 yıl önce

Jan Desktop v0.7.7 is live 💛 This update brings native MLX support on macOS, a broader UX and UI refresh across the app, and better support for developer workflows. You can now upload files in Projects, use the local API server with both local and remote models, and work more smoothly with tools like Claude Code and other CLIs. Update your Jan or download the latest version at
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Jan Desktop v0.7.7 is live 💛 This update brings native MLX support on macOS, a broader UX and UI refresh across the app, and better support for developer workflows. You can now upload files in Projects, use the local API server with both local and remote models, and work more smoothly with tools like Claude Code and other CLIs. Update your Jan or download the latest version at

👋 Jan

28,378 görüntüleme • 5 ay önce

The leading model runnable on a single cloud H100 GPU now fits on a single home GPU! 🔥 We've optimized Gemma 3 27B with QAT so you can run our best-in-class open model on your desktop RTX 3090 or similar. See how easy it is to try via ollama! 👇
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The leading model runnable on a single cloud H100 GPU now fits on a single home GPU! 🔥 We've optimized Gemma 3 27B with QAT so you can run our best-in-class open model on your desktop RTX 3090 or similar. See how easy it is to try via ollama! 👇

Glenn Cameron Jr

81,427 görüntüleme • 1 yıl önce

Gemma 4 is here! Our most intelligent open models to date, are built on the same world-class research and tech as Gemini 3, and are sized to run and fine-tune efficiently on local hardware. Check out what Google Gemma 4 brings to devs: 💎 Advanced Reasoning: Deep logic tasks, complex multi-step planning, and beyond 💎 Longer context: Seamlessly analyze entire codebases with context windows of 128K tokens for our edge models and 256K tokens for our largest models 💎 Vision and audio: Rich, multimodal interactions out of the box 💎 140+ languages: Trained on 140+ languages 💎 Apache 2.0 license: industry-standard open-source license
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Gemma 4 is here! Our most intelligent open models to date, are built on the same world-class research and tech as Gemini 3, and are sized to run and fine-tune efficiently on local hardware. Check out what Google Gemma 4 brings to devs: 💎 Advanced Reasoning: Deep logic tasks, complex multi-step planning, and beyond 💎 Longer context: Seamlessly analyze entire codebases with context windows of 128K tokens for our edge models and 256K tokens for our largest models 💎 Vision and audio: Rich, multimodal interactions out of the box 💎 140+ languages: Trained on 140+ languages 💎 Apache 2.0 license: industry-standard open-source license

Google for Developers

269,657 görüntüleme • 3 ay önce

Right now, you may not have access to models like GPT‑5.6 Sol, GPT‑4.6 Terra, GPT‑5.6 Luna, Claude Mythos 5, or Claude Fable 5. But you can run something surprisingly powerful today, locally, and completely free. in the next 10 mins on your 8 GB VRAM gaming laptop. Gemma 4 26B A4B QAT (MoE) delivers strong performance on a standard 8 GB VRAM GPU using Ollama, with no API, no usage limits, and no external dependencies. Out of the box, it reaches around 20 tokens per second without any optimizations. Only one command in your terminal: Ollama run gemma4:26b This means: Full offline capability (privacy by default) Zero recurring cost Competitive performance for many real world tasks Fast enough for interactive use on cheap consumer hardware If you're waiting for cutting edge cloud models, you're missing what is already practical today: a capable, local LLM that runs entirely on your own machine.
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Right now, you may not have access to models like GPT‑5.6 Sol, GPT‑4.6 Terra, GPT‑5.6 Luna, Claude Mythos 5, or Claude Fable 5. But you can run something surprisingly powerful today, locally, and completely free. in the next 10 mins on your 8 GB VRAM gaming laptop. Gemma 4 26B A4B QAT (MoE) delivers strong performance on a standard 8 GB VRAM GPU using Ollama, with no API, no usage limits, and no external dependencies. Out of the box, it reaches around 20 tokens per second without any optimizations. Only one command in your terminal: Ollama run gemma4:26b This means: Full offline capability (privacy by default) Zero recurring cost Competitive performance for many real world tasks Fast enough for interactive use on cheap consumer hardware If you're waiting for cutting edge cloud models, you're missing what is already practical today: a capable, local LLM that runs entirely on your own machine.

Alok

64,883 görüntüleme • 21 gün önce

Claude fable 5 is cooked Claude fable 5 Vs Gemma 4 26b a4b qat MTP Gemma 4 26b running locally on my 8GB vram single RTX 4060 built this using three.js in a single session and 3 prompts. no cloud, no subscription 100% private unlimited use. how long until it can catch up completely?
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Claude fable 5 is cooked Claude fable 5 Vs Gemma 4 26b a4b qat MTP Gemma 4 26b running locally on my 8GB vram single RTX 4060 built this using three.js in a single session and 3 prompts. no cloud, no subscription 100% private unlimited use. how long until it can catch up completely?

Alok

30,782 görüntüleme • 1 ay önce

wow, this new AI is incredible Promptly can generate prompts for specific AI models like ChatGPT, Midjourney, many video generators and.. guide you how to make it better, this is super useful free to use now 7 examples:
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wow, this new AI is incredible Promptly can generate prompts for specific AI models like ChatGPT, Midjourney, many video generators and.. guide you how to make it better, this is super useful free to use now 7 examples:

el.cine

130,220 görüntüleme • 1 yıl önce

🚨 do you understand what is happening?! OpenAI and Anthropic are putting the best models behind approval lists. Meanwhile GLM 5.2 is running locally on a Mac Studio, coding in a loop 24/7. If someone can turn off your AI, you are renting your intelligence layer. Local models are getting so good now that you can create gameplays like this.👇
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🚨 do you understand what is happening?! OpenAI and Anthropic are putting the best models behind approval lists. Meanwhile GLM 5.2 is running locally on a Mac Studio, coding in a loop 24/7. If someone can turn off your AI, you are renting your intelligence layer. Local models are getting so good now that you can create gameplays like this.👇

Vadim

14,609 görüntüleme • 18 gün önce

MRC is already deployed across all of OpenAI’s largest supercomputers that we use to train frontier models, including our site with Oracle Cloud Infrastructure (OCI) in Abilene, Texas, and in Microsoft’s Fairwater supercomputers. MRC is now available through the Open Compute Project for the entire industry to use and build on.
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MRC is already deployed across all of OpenAI’s largest supercomputers that we use to train frontier models, including our site with Oracle Cloud Infrastructure (OCI) in Abilene, Texas, and in Microsoft’s Fairwater supercomputers. MRC is now available through the Open Compute Project for the entire industry to use and build on.

OpenAI

145,781 görüntüleme • 2 ay önce

Our open-source RAG app, Verba, can now run Ollama models locally to embed documents into Weaviate and generate answers without your data leaving your device! I tested it with Llama3, and it works great + super quickly on my M2; In this recording, I'm doing a little Verba-ception, asking Verba what Verba is 🤤 You can also use open-source models like Mistral, Claude, or your own custom LLMs. This will make doing RAG with sensitive data possible since you won't depend on APIs anymore. Looking forward to everyone trying it out 🤗 Update's coming next week!
0:15

Our open-source RAG app, Verba, can now run Ollama models locally to embed documents into Weaviate and generate answers without your data leaving your device! I tested it with Llama3, and it works great + super quickly on my M2; In this recording, I'm doing a little Verba-ception, asking Verba what Verba is 🤤 You can also use open-source models like Mistral, Claude, or your own custom LLMs. This will make doing RAG with sensitive data possible since you won't depend on APIs anymore. Looking forward to everyone trying it out 🤗 Update's coming next week!

Edward

125,565 görüntüleme • 2 yıl önce

Introducing Jan v3, with updates to Jan Desktop v0.7.6 💛 Jan v3 is our first v3 model, a 4B base built for fine-tuning and fast local use, with stronger math and coding. This release also includes a small Jan Desktop update, starting with a UI refresh as we move toward a more unified Jan experience. Try it: - Jan v3 is available in Jan Desktop and at - Get the latest desktop app at Model: - Jan-v3-4B: - Jan-v3-4B-GGUF: Thanks Qwen for the base model and Georgi Gerganov for llama.cpp 💛
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Introducing Jan v3, with updates to Jan Desktop v0.7.6 💛 Jan v3 is our first v3 model, a 4B base built for fine-tuning and fast local use, with stronger math and coding. This release also includes a small Jan Desktop update, starting with a UI refresh as we move toward a more unified Jan experience. Try it: - Jan v3 is available in Jan Desktop and at - Get the latest desktop app at Model: - Jan-v3-4B: - Jan-v3-4B-GGUF: Thanks Qwen for the base model and Georgi Gerganov for llama.cpp 💛

👋 Jan

53,898 görüntüleme • 5 ay önce

Throughout my journey in developing multimodal models, I’ve always wanted a framework that lets me plug & play modality encoders/decoders on top of an auto-regressive LLM. I want to prototype fast, try new architectures, and have my demo files scale effortlessly — with full support for parallelism and optimization. Not just to hack⚙️, but also to scale🚀. So finally we built it for ourselves. LMMs-Engine: a lean, efficient framework built to train unified multimodal model at scale. From Qwen LLM, VLM, LLaVA-OV, and WanVideo, to unified models like Qwen-Omni and BAGEL — plus Linear-Attn GDN and research prototypes like RAE and SiT - all under one modular system that seamlessly integrates diverse datasets and optimization strategies. Powered by FSDP2 multi-dim parallelism, Ulysses sequence parallel, Flash-Attention, Liger Kernels, and Native Sparse Attention (also with bonus support for the Muon optimizer for all models).
0:19

Throughout my journey in developing multimodal models, I’ve always wanted a framework that lets me plug & play modality encoders/decoders on top of an auto-regressive LLM. I want to prototype fast, try new architectures, and have my demo files scale effortlessly — with full support for parallelism and optimization. Not just to hack⚙️, but also to scale🚀. So finally we built it for ourselves. LMMs-Engine: a lean, efficient framework built to train unified multimodal model at scale. From Qwen LLM, VLM, LLaVA-OV, and WanVideo, to unified models like Qwen-Omni and BAGEL — plus Linear-Attn GDN and research prototypes like RAE and SiT - all under one modular system that seamlessly integrates diverse datasets and optimization strategies. Powered by FSDP2 multi-dim parallelism, Ulysses sequence parallel, Flash-Attention, Liger Kernels, and Native Sparse Attention (also with bonus support for the Muon optimizer for all models).

Brian Li

54,768 görüntüleme • 8 ay önce

My Coloso course is officially open!🎉 Thank you everyone for your support! And thank you ye_jji for allowing me to use your art. You can find the link to my course in my bio where you can learn how to rig posed Live2D models like this! #vtuber
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My Coloso course is officially open!🎉 Thank you everyone for your support! And thank you ye_jji for allowing me to use your art. You can find the link to my course in my bio where you can learn how to rig posed Live2D models like this! #vtuber

ChaosV (Live2D Commissions)

136,676 görüntüleme • 7 ay önce

Today, Nesa is excited to announce cross-chain support with Sei. As part of this new development, Nesa will be featuring a dedicated ramp for Sei’s rich ecosystem of applications to seamlessly integrate with AI. Now any Sei dapp can run AI inference on hundreds of models supported by Nesa, including the largest LLMs and most popular models across Vision, Language, and Generative AI. For developers, we’ll have information soon on how to access AI inference on Nesa via smart contracts from the Sei blockchain. Stay tuned for more details on this ground breaking development for decentralized AI.
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Today, Nesa is excited to announce cross-chain support with Sei. As part of this new development, Nesa will be featuring a dedicated ramp for Sei’s rich ecosystem of applications to seamlessly integrate with AI. Now any Sei dapp can run AI inference on hundreds of models supported by Nesa, including the largest LLMs and most popular models across Vision, Language, and Generative AI. For developers, we’ll have information soon on how to access AI inference on Nesa via smart contracts from the Sei blockchain. Stay tuned for more details on this ground breaking development for decentralized AI.

Nesa

79,657 görüntüleme • 2 yıl önce

Jan Desktop v0.7.8 is out 👋 You can now run OpenClaw agents with local models, in just a few clicks. Plus Jan CLI for your workflows, and automatic context management so you never get cut off mid-conversation. Agent support is still experimental. We're working hard on it and would love your feedback 💛 Download Jan:
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Jan Desktop v0.7.8 is out 👋 You can now run OpenClaw agents with local models, in just a few clicks. Plus Jan CLI for your workflows, and automatic context management so you never get cut off mid-conversation. Agent support is still experimental. We're working hard on it and would love your feedback 💛 Download Jan:

👋 Jan

16,680 görüntüleme • 4 ay önce