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A catalogue is useless if you can’t run it. ⬟ The Playground is executable. Models are live, not listed. 100k+ models available for real inference. No local setup required. Browse less. Execute more.

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Nesa

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15,378 просмотров • 7 месяцев назад •via X (Twitter)

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The Playground Is the New Frontier ⬟ Every era of computing starts with a frontier. For decentralized AI, it’s called the Playground. This upcoming interface is where decentralized intelligence goes live: real models, real encryption, real rewards and more. Proof you can see, privacy you can trust.
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The Playground Is the New Frontier ⬟ Every era of computing starts with a frontier. For decentralized AI, it’s called the Playground. This upcoming interface is where decentralized intelligence goes live: real models, real encryption, real rewards and more. Proof you can see, privacy you can trust.

Nesa

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Microsoft killed the GPU mafia 🤯 They finally open-sourced their 1-bit LLM inference framework called bitnet.cpp. It lets you run 100B parameter models on your local CPU without GPUs. - 6.17x faster inference - 82.2% less energy on CPUs 100% Open Source.
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Microsoft killed the GPU mafia 🤯 They finally open-sourced their 1-bit LLM inference framework called bitnet.cpp. It lets you run 100B parameter models on your local CPU without GPUs. - 6.17x faster inference - 82.2% less energy on CPUs 100% Open Source.

Oliver Prompts

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Our new Mistral AI playground is now live! 🔥 You can now quickly test our models in the playground and switch easily from UX to code. Try it out and more exciting features coming soon!
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Our new Mistral AI playground is now live! 🔥 You can now quickly test our models in the playground and switch easily from UX to code. Try it out and more exciting features coming soon!

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This is less than 100k crowd and if you think the crowd was more than this then I can’t help you. Credit Dr. Rocky
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This is less than 100k crowd and if you think the crowd was more than this then I can’t help you. Credit Dr. Rocky

THE ORDINARY MP🎭

567,417 просмотров • 10 месяцев назад

70% of AI compute in 2026 is inference. Not training. The models are built. The real infrastructure challenge is serving them at scale to millions of users and agents, every day, in production. Most enterprise infrastructure is still optimized for the wrong workload.🧵
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70% of AI compute in 2026 is inference. Not training. The models are built. The real infrastructure challenge is serving them at scale to millions of users and agents, every day, in production. Most enterprise infrastructure is still optimized for the wrong workload.🧵

Aethir

21,171 просмотров • 2 месяцев назад

90% of "AI developers" just download pre packaged GGUF files from Hugging Face, hit run, and call it a day. The top 10% know how to pull the raw safetensors, run the math, and quantize massive models into Q4_K_M themselves. If you think llama.cpp can only execute models, you’re missing the best part of the open source ecosystem. It’s a high performance optimization suite. Manually stripping 69% of the VRAM footprint off a brand new model architecture is where real infrastructure value is made. If you want to actually master local inference and deploy models like Google’s massive Gemma 4 12B it on consumer NVIDIA hardware using llama.cpp, you need to learn this pipeline. Let's build it. I just took the raw 22.7 GB Gemma 4 baseline and manually compressed it down to a 7.02 GB Q4_K_M GGUF artifact using llama.cpp. That is a 69% reduction in footprint. No quality loss. No VRAM bottlenecks. Just native, hardware accelerated C++ inference running a full 2,50,000 token context window on a dual NVIDIA Tesla T4 setup. Stop melting your VRAM on unoptimized weights and stop relying on other people's pipelines. Own your stack. I mapped this entire architecture from dynamic binary fetching to raw quantization and real time GPU streaming into a single, bulletproof notebook. Notebook link is in the comments below. Bookmark this blueprint for your next deployment and tell me which quantization works best for your workflow and model.
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90% of "AI developers" just download pre packaged GGUF files from Hugging Face, hit run, and call it a day. The top 10% know how to pull the raw safetensors, run the math, and quantize massive models into Q4_K_M themselves. If you think llama.cpp can only execute models, you’re missing the best part of the open source ecosystem. It’s a high performance optimization suite. Manually stripping 69% of the VRAM footprint off a brand new model architecture is where real infrastructure value is made. If you want to actually master local inference and deploy models like Google’s massive Gemma 4 12B it on consumer NVIDIA hardware using llama.cpp, you need to learn this pipeline. Let's build it. I just took the raw 22.7 GB Gemma 4 baseline and manually compressed it down to a 7.02 GB Q4_K_M GGUF artifact using llama.cpp. That is a 69% reduction in footprint. No quality loss. No VRAM bottlenecks. Just native, hardware accelerated C++ inference running a full 2,50,000 token context window on a dual NVIDIA Tesla T4 setup. Stop melting your VRAM on unoptimized weights and stop relying on other people's pipelines. Own your stack. I mapped this entire architecture from dynamic binary fetching to raw quantization and real time GPU streaming into a single, bulletproof notebook. Notebook link is in the comments below. Bookmark this blueprint for your next deployment and tell me which quantization works best for your workflow and model.

Alok

62,631 просмотров • 1 месяц назад

SEVEN RTX 3090S IN A WATER TANK FOR AI SERVER it is a private AI server with the power bill moved into your room. not a clean Mac mini. not a quiet box under a monitor. loose vertical GPUs sit inside a transparent tank. bubbles rise through distilled water. ALLIED CONTROL is printed on the side. it looks closer to a lab accident than a normal workstation. but the logic is obvious: seven RTX 3090s = seven 24GB cards. that is the used-market shortcut for people who want local inference without paying cloud tax on every run. put Ollama, llama.cpp, vLLM, Open WebUI, Tailscale, Qwen, DeepSeek, or Llama on top. now the box can handle client files, code agents, scraping jobs, evals, transcription, and boring overnight work. not because it beats frontier cloud models. because it changes the bill shape. no rate limit. no per-token anxiety. no sensitive client context leaving the building. no monthly stack quietly turning into rent. the ugly part is physical. seven 3090s can pull serious power, dump serious heat, and punish lazy cooling. distilled water is the weird visual, not a setup tip. real immersion rigs live or die on coolant chemistry, insulation, pumps, maintenance, and whether the room can handle the heat. local AI PCs are becoming less like gaming builds and more like small private data centers. the early question is not: can it run ChatGPT? it is: what work is repetitive, private, expensive in the cloud, and worth owning in hardware?
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SEVEN RTX 3090S IN A WATER TANK FOR AI SERVER it is a private AI server with the power bill moved into your room. not a clean Mac mini. not a quiet box under a monitor. loose vertical GPUs sit inside a transparent tank. bubbles rise through distilled water. ALLIED CONTROL is printed on the side. it looks closer to a lab accident than a normal workstation. but the logic is obvious: seven RTX 3090s = seven 24GB cards. that is the used-market shortcut for people who want local inference without paying cloud tax on every run. put Ollama, llama.cpp, vLLM, Open WebUI, Tailscale, Qwen, DeepSeek, or Llama on top. now the box can handle client files, code agents, scraping jobs, evals, transcription, and boring overnight work. not because it beats frontier cloud models. because it changes the bill shape. no rate limit. no per-token anxiety. no sensitive client context leaving the building. no monthly stack quietly turning into rent. the ugly part is physical. seven 3090s can pull serious power, dump serious heat, and punish lazy cooling. distilled water is the weird visual, not a setup tip. real immersion rigs live or die on coolant chemistry, insulation, pumps, maintenance, and whether the room can handle the heat. local AI PCs are becoming less like gaming builds and more like small private data centers. the early question is not: can it run ChatGPT? it is: what work is repetitive, private, expensive in the cloud, and worth owning in hardware?

kocer

591,487 просмотров • 1 месяц назад

If you can imagine it, you can generate it! The best thing about video models is that you can let your imagination run wild like never before. Prompt ⤵️
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If you can imagine it, you can generate it! The best thing about video models is that you can let your imagination run wild like never before. Prompt ⤵️

Umesh

87,346 просмотров • 7 месяцев назад

🚨 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.👇

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Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at hello@qualiastudios.dev More soon
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Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at [email protected] More soon

Qualia

87,750 просмотров • 2 месяцев назад

Go local: ollama is here in Raycast 🦙 The power of Raycast AI, fully offline! Perfect for coding on flights or going completely incognito. Local models are free for everyone. No subscription needed.
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Go local: ollama is here in Raycast 🦙 The power of Raycast AI, fully offline! Perfect for coding on flights or going completely incognito. Local models are free for everyone. No subscription needed.

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54,002 просмотров • 1 год назад

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People say running is bad and that it makes you look old and wastes away your muscle People are dumb That only happens if you run for to long at to high of a heart rate If you run at 130-140 beats per minute with a smile on your face it’s actually some of the best therapy there is If you are running and you can’t smile and it looks like you are in agony and can’t hold a pleasant conversation you are doing it wrong and that’s what will cause you to look old and frail This is called “the sweet spot” folks and it can be used for way more than just running

Thor Torrens

19,510 просмотров • 5 месяцев назад

You don’t need a data center to support private AI. ⬟ Private inference doesn’t live in one place. It runs across the network. If your device is online, it can contribute to privacy-preserving execution. Run a node on the Nesa network.
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You don’t need a data center to support private AI. ⬟ Private inference doesn’t live in one place. It runs across the network. If your device is online, it can contribute to privacy-preserving execution. Run a node on the Nesa network.

Nesa

28,966 просмотров • 8 месяцев назад

$28k/day ads look like 10/10 models now no studio, no crew, no real creator and you still can’t tell it’s ai natural lighting, skin texture, imperfect details it feels like a real skincare routine that’s why it works no overacting, no forced hooks, no “ad energy” just calm, believable usage people don’t question it, they trust it same script → dozens of faces, tones, environments each one hits a slightly different audience this is what scalable ugc looks like now rt + comment “realugc” and i’ll send the setup (follow for dm)
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$28k/day ads look like 10/10 models now no studio, no crew, no real creator and you still can’t tell it’s ai natural lighting, skin texture, imperfect details it feels like a real skincare routine that’s why it works no overacting, no forced hooks, no “ad energy” just calm, believable usage people don’t question it, they trust it same script → dozens of faces, tones, environments each one hits a slightly different audience this is what scalable ugc looks like now rt + comment “realugc” and i’ll send the setup (follow for dm)

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Frame mogged to oblivion 💀 This is GPT 5.4 not even pro.. In all seriousness these are videos of older models — this video was readily available so I thought it would be fun to compare how much we’ve improved in less than a year!
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Frame mogged to oblivion 💀 This is GPT 5.4 not even pro.. In all seriousness these are videos of older models — this video was readily available so I thought it would be fun to compare how much we’ve improved in less than a year!

Chris

250,557 просмотров • 5 месяцев назад

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Excited to annouce that @askvenice is now integrated as our sole LLM inference provider for bunnyCompute. We love the product and recommend it for any LLM use case. Open-source models, no data retention, no censorship - that's why we chose them.

BunnyOS

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Today only, Toxic Town billboards are using real time data to show what air quality is like across the country. If the air quality is “good” you will see a full poster for the series. If the air quality is “poor”, we are sacrificing our billboards to be covered in a cloud of white smoke. Just because you can’t see it, doesn’t mean it’s not happening.
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Today only, Toxic Town billboards are using real time data to show what air quality is like across the country. If the air quality is “good” you will see a full poster for the series. If the air quality is “poor”, we are sacrificing our billboards to be covered in a cloud of white smoke. Just because you can’t see it, doesn’t mean it’s not happening.

Netflix UK & Ireland

92,534 просмотров • 1 год назад

⭐The Year of Inference is here. Featherless is now an official inference provider on Hugging Face, unlocking 6,700+ LLMs for anyone to run, eval, and deploy instantly. It all starts with accessibility. From DeepSeek to Mistral, LLaMA to Qwen — powerful LLMs are one click away. We believe the future of AI is shaped by the long tail: personalized, specialized models tuned to real people’s needs. To get there, inference must be open, affordable, and usable by all. Whether you're fine-tuning, prototyping, or scaling a product, this moment is for you. 🫱🏻‍🫲🏻Let’s make inference the easiest part of building with AI. 📢 Share this so more builders know what’s now possible. Excited to be partnering with clem 🤗 Julien Chaumond Vaibhav (VB) Srivastav Simon Brandeis & Hugging Face team to take this to the next level!
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⭐The Year of Inference is here. Featherless is now an official inference provider on Hugging Face, unlocking 6,700+ LLMs for anyone to run, eval, and deploy instantly. It all starts with accessibility. From DeepSeek to Mistral, LLaMA to Qwen — powerful LLMs are one click away. We believe the future of AI is shaped by the long tail: personalized, specialized models tuned to real people’s needs. To get there, inference must be open, affordable, and usable by all. Whether you're fine-tuning, prototyping, or scaling a product, this moment is for you. 🫱🏻‍🫲🏻Let’s make inference the easiest part of building with AI. 📢 Share this so more builders know what’s now possible. Excited to be partnering with clem 🤗 Julien Chaumond Vaibhav (VB) Srivastav Simon Brandeis & Hugging Face team to take this to the next level!

Featherless AI

24,012 просмотров • 1 год назад

world models have their comfyui now. introducing alakazam studio, the first local, open source UI for world models. •⁠ ⁠sentence goes in => you edit the state graph => play •⁠ ⁠on a live model, yours, running in your browser •⁠ ⁠⁠apache-2.0, fully open source fork it and point it at your model 👇
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world models have their comfyui now. introducing alakazam studio, the first local, open source UI for world models. •⁠ ⁠sentence goes in => you edit the state graph => play •⁠ ⁠on a live model, yours, running in your browser •⁠ ⁠⁠apache-2.0, fully open source fork it and point it at your model 👇

hugo

25,362 просмотров • 12 дней назад