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GPT-5? Frontier models? You don’t train titans on toy rigs. Exabits is your GPU mothership—scalable, no waitlists, no gatekeepers, and built for LLM liftoff. Plug in. Power up.

Exabits

104,293 subscribers

18,121 次观看 • 10 个月前 •via X (Twitter)

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OSS devs shouldn’t have to beg for compute. Exabits is the launchpad for open-source AI to go orbital. Training on Exabits means: ✅ No throttling ✅ No permission slips ✅ No infra bottlenecks Just plug in and scale.

OSS devs shouldn’t have to beg for compute. Exabits is the launchpad for open-source AI to go orbital. Training on Exabits means: ✅ No throttling ✅ No permission slips ✅ No infra bottlenecks Just plug in and scale.

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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.

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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“You don’t quit and you don’t make excuses,” Tom Brady Toughness is built in your willingness to fight no matter what the situation is.

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BlackBird is now on Windows! Spin up powerful AI agents in just a click. Train models locally, privately, and offline, right from your laptop. Download now: The full power of AI is now in your hands.

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MESSIER | Horizon The compliance first anonymization tool enabling private token transfers is expanding. 📢 Project owners and degens, wake up! Vote to List is now live. Submit your token. Rally your army. Hit 100 votes and claim your spot. No gatekeepers. No fees. Just pure community power deciding what gets listed. Be early or watch others take your spot. Get listed on Horizon and unlock compliance first private transfers with built in tax friendly statements. 👉 Go to:

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After the Humans came the warriors. The Sentinels were built for one thing: the fight. Their power is a permanent 20% discount on every spell and boost in Miner Wars, so you can power up more often without burning through your resources. Tougher. Sharper. Built to win. ⚔️What is your go-to strategy for climbing the ranks in Miner Wars?

After the Humans came the warriors. The Sentinels were built for one thing: the fight. Their power is a permanent 20% discount on every spell and boost in Miner Wars, so you can power up more often without burning through your resources. Tougher. Sharper. Built to win. ⚔️What is your go-to strategy for climbing the ranks in Miner Wars?

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Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below

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🚀 Hyra AI app just leveled up! Optimized for performance, built for passive yield. With an enhanced training engine and smoother UX, earning $HYRA on your device is now more efficient than ever. 🧠 Plug into edge AI. 💸 Train-to-Earn in the background. 📈 Let your phone generate real on-chain value. Update and start earning now: 🍎iOS: 📱Android:

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Mondo is the most adorable companion robot. It’s safe around kids, can track and follow a person, and capture high-resolution action videos. Mondo is also doing frontier research in humanoid Video-Action models built on a world model backbone: I have no doubt we’ll be hearing this name a lot in consumer robotics. Thanks Mondo Robotics Shuo Yang for the tour.

Mondo is the most adorable companion robot. It’s safe around kids, can track and follow a person, and capture high-resolution action videos. Mondo is also doing frontier research in humanoid Video-Action models built on a world model backbone: I have no doubt we’ll be hearing this name a lot in consumer robotics. Thanks Mondo Robotics Shuo Yang for the tour.

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🚨 Alibaba just open sourced a GUI agent that lives inside your webpage and controls it with natural language. It's called Page Agent and it's not a browser extension. It's pure JavaScript no Python, no Puppeteer, no headless browser, no screenshots. Just one script tag and your web app understands natural language. Here's what it actually does: → Embed it with a single tag or npm install → Control any web interface with plain English commands → Text-based DOM manipulation no OCR, no vision models needed → Bring your own LLM (GPT, Claude, Qwen, anything) → Ships a built-in UI with human-in-the-loop support → Turn 20-click ERP/CRM workflows into one sentence → Optional Chrome extension for multi-tab agent tasks → Works on any web app SaaS, admin panels, internal tools Companies are charging $30/month for AI copilots built on this exact idea. This is 3 lines of code. Your users. Your interface. The AI copilot layer for every web app just got open sourced. 1.6K stars. 100% Open Source. (Link in the comments)

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Kani your just mixing up up your own words now i don’t need anything to fit “my narrative” because you said it and as i said the original clip was focused on everything u said about Silky you just backtracking for no reason, but there is no reason to respond you “cleared” your name.

Kani your just mixing up up your own words now i don’t need anything to fit “my narrative” because you said it and as i said the original clip was focused on everything u said about Silky you just backtracking for no reason, but there is no reason to respond you “cleared” your name.

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The rise in delayed steals is a direct result of catchers reading runners. If you adjust your stance on runner/no runner, you HAVE to train for situations like these.

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Xan Barksdale

376,117 次观看 • 1 年前

Holy shit... Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU. It's called BitNet. And it does what was supposed to be impossible. No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed. Here's how it works: Every other LLM stores weights in 32-bit or 16-bit floats. BitNet uses 1.58 bits. Weights are ternary just -1, 0, or +1. That's it. No floats. No expensive matrix math. Pure integer operations your CPU was already built for. The result: - 100B model runs on a single CPU at 5-7 tokens/second - 2.37x to 6.17x faster than llama.cpp on x86 - 82% lower energy consumption on x86 CPUs - 1.37x to 5.07x speedup on ARM (your MacBook) - Memory drops by 16-32x vs full-precision models The wildest part: Accuracy barely moves. BitNet b1.58 2B4T their flagship model was trained on 4 trillion tokens and benchmarks competitively against full-precision models of the same size. The quantization isn't destroying quality. It's just removing the bloat. What this actually means: - Run AI completely offline. Your data never leaves your machine - Deploy LLMs on phones, IoT devices, edge hardware - No more cloud API bills for inference - AI in regions with no reliable internet The model supports ARM and x86. Works on your MacBook, your Linux box, your Windows machine. 27.4K GitHub stars. 2.2K forks. Built by Microsoft Research. 100% Open Source. MIT License.

Holy shit... Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU. It's called BitNet. And it does what was supposed to be impossible. No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed. Here's how it works: Every other LLM stores weights in 32-bit or 16-bit floats. BitNet uses 1.58 bits. Weights are ternary just -1, 0, or +1. That's it. No floats. No expensive matrix math. Pure integer operations your CPU was already built for. The result: - 100B model runs on a single CPU at 5-7 tokens/second - 2.37x to 6.17x faster than llama.cpp on x86 - 82% lower energy consumption on x86 CPUs - 1.37x to 5.07x speedup on ARM (your MacBook) - Memory drops by 16-32x vs full-precision models The wildest part: Accuracy barely moves. BitNet b1.58 2B4T their flagship model was trained on 4 trillion tokens and benchmarks competitively against full-precision models of the same size. The quantization isn't destroying quality. It's just removing the bloat. What this actually means: - Run AI completely offline. Your data never leaves your machine - Deploy LLMs on phones, IoT devices, edge hardware - No more cloud API bills for inference - AI in regions with no reliable internet The model supports ARM and x86. Works on your MacBook, your Linux box, your Windows machine. 27.4K GitHub stars. 2.2K forks. Built by Microsoft Research. 100% Open Source. MIT License.

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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

54,840 次观看 • 9 个月前

This tool is literally Higgsfield AI but FREE for good. It's called Wan2GP. A full AI video studio built specifically for people without expensive hardware. Runs on as little as 6GB of VRAM, even old RTX 10-series cards and 8GB laptops. Everything stays on your machine, no uploads, no caps, no watermarks. What you get in one app: • Text-to-video and image-to-video generation • The best open models built in: Wan 2.2, LTX-2, Hunyuan Video, Flux • A full browser interface with a queue system • LoRA support to customize any model • Mask editor and prompt enhancer included A 5-second clip generates in minutes on a mid-range gaming rig. No subscription, ever. 100% Free. Open Source.

This tool is literally Higgsfield AI but FREE for good. It's called Wan2GP. A full AI video studio built specifically for people without expensive hardware. Runs on as little as 6GB of VRAM, even old RTX 10-series cards and 8GB laptops. Everything stays on your machine, no uploads, no caps, no watermarks. What you get in one app: • Text-to-video and image-to-video generation • The best open models built in: Wan 2.2, LTX-2, Hunyuan Video, Flux • A full browser interface with a queue system • LoRA support to customize any model • Mask editor and prompt enhancer included A 5-second clip generates in minutes on a mid-range gaming rig. No subscription, ever. 100% Free. Open Source.

Simplifying AI

175,970 次观看 • 16 天前

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history

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12,437 次观看 • 3 个月前

Google Translate is cooked after this. A developer built a local AI translation engine that runs 40 languages entirely on your own laptop. It's called LibreTranslate. No API key. No usage limits. No sending your documents to Google's servers. You install it once. It runs forever. Here's what it handles: → Paste text. Translated instantly. → Drop in a file. Outputs the translated version. → Point it at a URL. Returns the page in your language. → Build it into your own app via its local REST API. The speed is not the story. The privacy is. Google Translate reads every sentence you paste into it. Legal contracts. Medical records. Internal emails. Client documents. Every word goes to their servers and stays there. LibreTranslate runs entirely offline. Nothing leaves your machine. Ever. The numbers: → 40 languages supported → Runs on CPU -- no GPU needed → Self-hosted in under 5 minutes → REST API built in for developers → 10K+ stars on GitHub 100% open source. MIT licensed. Price: $0. Google charges nothing for Translate either but it charges you something else. GitHub:

Google Translate is cooked after this. A developer built a local AI translation engine that runs 40 languages entirely on your own laptop. It's called LibreTranslate. No API key. No usage limits. No sending your documents to Google's servers. You install it once. It runs forever. Here's what it handles: → Paste text. Translated instantly. → Drop in a file. Outputs the translated version. → Point it at a URL. Returns the page in your language. → Build it into your own app via its local REST API. The speed is not the story. The privacy is. Google Translate reads every sentence you paste into it. Legal contracts. Medical records. Internal emails. Client documents. Every word goes to their servers and stays there. LibreTranslate runs entirely offline. Nothing leaves your machine. Ever. The numbers: → 40 languages supported → Runs on CPU -- no GPU needed → Self-hosted in under 5 minutes → REST API built in for developers → 10K+ stars on GitHub 100% open source. MIT licensed. Price: $0. Google charges nothing for Translate either but it charges you something else. GitHub:

Rimsha Bhardwaj

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Tired of trading electricity in a system built for institutions — not you? Carlos Aurelio Hernández felt the same. That’s why he went on a mission — to build a platform where energy professionals could finally trade on their own terms. Now, as CEO of Watt2Trade, he’s changing the game. Here’s how... ⚡🧵 Before building Watt2Trade, Carlos became one of the most respected voices in Mexico’s energy sector — with 35+ media appearances on platforms like Forbes, El Financiero, and Grupo Fórmula. He’s been at the table for every major energy discussion in the last decade. And more importantly — he’s built... ⚙️ HHGM – powering factories, refineries, and municipalities ⚡ SUJIO – cutting energy costs by up to 30% 💼 Volta Capital – backing the next wave of energy innovation Now Carlos is leading Watt2Trade — the first decentralized exchange where you can trade electricity directly. ✅ No brokers ✅ No approvals ✅ No red tape Just your wallet, your power — and a global marketplace open 24/7. It’s built by people who understand the energy market inside and out — and are finally putting it in your hands. This is the future of energy — and you’re invited to shape it. Your kilowatt is your currency. Your Watt is your Power.

Tired of trading electricity in a system built for institutions — not you? Carlos Aurelio Hernández felt the same. That’s why he went on a mission — to build a platform where energy professionals could finally trade on their own terms. Now, as CEO of Watt2Trade, he’s changing the game. Here’s how... ⚡🧵 Before building Watt2Trade, Carlos became one of the most respected voices in Mexico’s energy sector — with 35+ media appearances on platforms like Forbes, El Financiero, and Grupo Fórmula. He’s been at the table for every major energy discussion in the last decade. And more importantly — he’s built... ⚙️ HHGM – powering factories, refineries, and municipalities ⚡ SUJIO – cutting energy costs by up to 30% 💼 Volta Capital – backing the next wave of energy innovation Now Carlos is leading Watt2Trade — the first decentralized exchange where you can trade electricity directly. ✅ No brokers ✅ No approvals ✅ No red tape Just your wallet, your power — and a global marketplace open 24/7. It’s built by people who understand the energy market inside and out — and are finally putting it in your hands. This is the future of energy — and you’re invited to shape it. Your kilowatt is your currency. Your Watt is your Power.

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28,792 次观看 • 1 年前