OpenAI CEO says it's 'quite terrible' for your PC to have RAM — Sam Altman says data centers offer better utilization #Technology #AI #AIHardware #openai #samaltman #datacenters #localinference #cheekypint
OpenAI CEO says it's 'quite terrible' for your PC to have RAM — Sam Altman says data centers offer better utilization
OpenAI CEO Sam Altman has data centers full of memory, but seemingly it's the 32GB of RAM in your desktop that's the problem. In an interview over beers with the YouTube channel Cheeky Pint, Altman...
puretech.news
October 30, 2026 at 9:52 PM
OpenAI CEO says it's 'quite terrible' for your PC to have RAM — Sam Altman says data centers offer better utilization #Technology #AI #AIHardware #openai #samaltman #datacenters #localinference #cheekypint
Local AI models running on laptops have become more accessible with the GGUF file format, making local inference easier than ever. #AI #GGUF #LocalInference 🤖👨💻
Transformers now runs llama.cpp quants
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
huggingface.co
October 19, 2026 at 2:40 PM
Local AI models running on laptops have become more accessible with the GGUF file format, making local inference easier than ever. #AI #GGUF #LocalInference 🤖👨💻
Microsoft demoed DeepSeek V4 Flash running on a laptop:
284B open-weight, quantized to 1.6 bits → ~60GB.
At 8 bits the same weights need ~284GB.
Memory, not compute, decides if it runs.
On-device inference doesn't kill the bill —
it changes its unit. #LocalInference
284B open-weight, quantized to 1.6 bits → ~60GB.
At 8 bits the same weights need ~284GB.
Memory, not compute, decides if it runs.
On-device inference doesn't kill the bill —
it changes its unit. #LocalInference
October 8, 2026 at 1:10 AM
Microsoft demoed DeepSeek V4 Flash running on a laptop:
284B open-weight, quantized to 1.6 bits → ~60GB.
At 8 bits the same weights need ~284GB.
Memory, not compute, decides if it runs.
On-device inference doesn't kill the bill —
it changes its unit. #LocalInference
284B open-weight, quantized to 1.6 bits → ~60GB.
At 8 bits the same weights need ~284GB.
Memory, not compute, decides if it runs.
On-device inference doesn't kill the bill —
it changes its unit. #LocalInference
Microsoft Surface Laptop Ultra: 128GB RAM for AI Devs
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https://nile1.com/microsoft-surface-laptop-ultra-128gb-ram-for-ai-devs/
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#128gbRam #aiDevelopers #largeLanguageModels #localInference #macbookPro #microsoft #surfaceLaptopStudio #surfaceLaptopUltra #unifiedMem
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https://nile1.com/microsoft-surface-laptop-ultra-128gb-ram-for-ai-devs/
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#128gbRam #aiDevelopers #largeLanguageModels #localInference #macbookPro #microsoft #surfaceLaptopStudio #surfaceLaptopUltra #unifiedMem
October 7, 2026 at 6:50 PM
Microsoft Surface Laptop Ultra: 128GB RAM for AI Devs
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https://nile1.com/microsoft-surface-laptop-ultra-128gb-ram-for-ai-devs/
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#128gbRam #aiDevelopers #largeLanguageModels #localInference #macbookPro #microsoft #surfaceLaptopStudio #surfaceLaptopUltra #unifiedMem
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https://nile1.com/microsoft-surface-laptop-ultra-128gb-ram-for-ai-devs/
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#128gbRam #aiDevelopers #largeLanguageModels #localInference #macbookPro #microsoft #surfaceLaptopStudio #surfaceLaptopUltra #unifiedMem
A new arXiv paper, HARISSA, uses a language model's own hidden states to decide which queries deserve extra compute and which are too risky to answer, helping small local models balance efficiency and safety without sending…
#EdgeAI #OnDeviceAI #LLM #LocalInference
https://arxiv.org/abs/2609.38006
#EdgeAI #OnDeviceAI #LLM #LocalInference
https://arxiv.org/abs/2609.38006
October 1, 2026 at 12:01 AM
A new arXiv paper, HARISSA, uses a language model's own hidden states to decide which queries deserve extra compute and which are too risky to answer, helping small local models balance efficiency and safety without sending…
#EdgeAI #OnDeviceAI #LLM #LocalInference
https://arxiv.org/abs/2609.38006
#EdgeAI #OnDeviceAI #LLM #LocalInference
https://arxiv.org/abs/2609.38006
Learn how to run a private, offline AI coding assistant with Atomic Chat on Linux. Install it, download a coding model, and code locally without cloud API keys.
Full guide here: ostechnix.com/atomic-chat-...
#AtomicChat #AI #CodingAgent #AIAgent #Opensource #Linux #Windows #Macos #LocalInference
Full guide here: ostechnix.com/atomic-chat-...
#AtomicChat #AI #CodingAgent #AIAgent #Opensource #Linux #Windows #Macos #LocalInference
Atomic Chat: Run a Private, Offline AI Coding Assistant - OSTechNix
Learn how to run a private, offline AI coding assistant with Atomic Chat on Linux. Install it, download a model, and code locally without cloud API keys.
ostechnix.com
September 18, 2026 at 3:54 PM
Learn how to run a private, offline AI coding assistant with Atomic Chat on Linux. Install it, download a coding model, and code locally without cloud API keys.
Full guide here: ostechnix.com/atomic-chat-...
#AtomicChat #AI #CodingAgent #AIAgent #Opensource #Linux #Windows #Macos #LocalInference
Full guide here: ostechnix.com/atomic-chat-...
#AtomicChat #AI #CodingAgent #AIAgent #Opensource #Linux #Windows #Macos #LocalInference
August 26, 2026 at 8:05 PM
By the numbers — local inference economics:
• Free for up to 2 nodes
• Zero per-token costs on your own hardware
• No rate limits beyond what your GPU can physically generate
• gemma-4-12b-qat fits a single 12–16GB GPU
#selfhosting #gpuoptimization #batchinference #localinference #gemma #homelab
• Free for up to 2 nodes
• Zero per-token costs on your own hardware
• No rate limits beyond what your GPU can physically generate
• gemma-4-12b-qat fits a single 12–16GB GPU
#selfhosting #gpuoptimization #batchinference #localinference #gemma #homelab
August 21, 2026 at 5:10 PM
By the numbers — local inference economics:
• Free for up to 2 nodes
• Zero per-token costs on your own hardware
• No rate limits beyond what your GPU can physically generate
• gemma-4-12b-qat fits a single 12–16GB GPU
#selfhosting #gpuoptimization #batchinference #localinference #gemma #homelab
• Free for up to 2 nodes
• Zero per-token costs on your own hardware
• No rate limits beyond what your GPU can physically generate
• gemma-4-12b-qat fits a single 12–16GB GPU
#selfhosting #gpuoptimization #batchinference #localinference #gemma #homelab
Unlocking Edge AI: How A Hybrid Data Architecture Can Power Local LLM Deployments
www.linkedin.com/pulse/unlock...
#AI #EdgeAI #EnterpriseAI #LocalLLM #Ollama #OpenWebUI #LocalInference #UnifiedDataManagement #UnstructuredData #UDM
www.linkedin.com/pulse/unlock...
#AI #EdgeAI #EnterpriseAI #LocalLLM #Ollama #OpenWebUI #LocalInference #UnifiedDataManagement #UnstructuredData #UDM
Unlocking Edge AI: How A Hybrid Data Architecture Can Power Local LLM Deployments
One of the great things about a hybrid unstructured data architecture is that data can be pinned to the edge in a particular location, even when people are working on that dataset on their edge nodes ...
www.linkedin.com
October 24, 2025 at 12:14 PM
Unlocking Edge AI: How A Hybrid Data Architecture Can Power Local LLM Deployments
www.linkedin.com/pulse/unlock...
#AI #EdgeAI #EnterpriseAI #LocalLLM #Ollama #OpenWebUI #LocalInference #UnifiedDataManagement #UnstructuredData #UDM
www.linkedin.com/pulse/unlock...
#AI #EdgeAI #EnterpriseAI #LocalLLM #Ollama #OpenWebUI #LocalInference #UnifiedDataManagement #UnstructuredData #UDM
Run massive AI locally! Use low-bit quantization (Q1 or Q2) to deploy high-parameter models up to 250B on consumer hardware. Maximize your performance by optimizing weight loading and inference efficiency. #AI #LLM #MachineLearning #LocalInference #Quantization https://ai.dappcrypto.org/r/bV
July 17, 2026 at 9:01 PM
Run massive AI locally! Use low-bit quantization (Q1 or Q2) to deploy high-parameter models up to 250B on consumer hardware. Maximize your performance by optimizing weight loading and inference efficiency. #AI #LLM #MachineLearning #LocalInference #Quantization https://ai.dappcrypto.org/r/bV
When I see this, and read the volume increases in tokens (it's in the tens of trillions), my first thought is that we've got to make local inference a first-class citizen of the AI ecosystem!
#ai #localinference #openrouter
OpenRouter Raises $113M Series B
openrouter.ai/announcement...
#ai #localinference #openrouter
OpenRouter Raises $113M Series B
openrouter.ai/announcement...
OpenRouter Raises $113M Series B | OpenRouter
OpenRouter has raised a $113M Series B led by CapitalG, with participation from NVentures, ServiceNow Ventures, MongoDB Ventures, Snowflake Ventures, Databricks
openrouter.ai
May 30, 2026 at 10:32 PM
When I see this, and read the volume increases in tokens (it's in the tens of trillions), my first thought is that we've got to make local inference a first-class citizen of the AI ecosystem!
#ai #localinference #openrouter
OpenRouter Raises $113M Series B
openrouter.ai/announcement...
#ai #localinference #openrouter
OpenRouter Raises $113M Series B
openrouter.ai/announcement...
Flash-MoE: Running a 397B Parameter Model on a Laptop - companion paper with the full details: github.com/danveloper/f... #localinference #ai #llms #ml #macbook #apple
github.com
March 22, 2026 at 6:31 PM
Flash-MoE: Running a 397B Parameter Model on a Laptop - companion paper with the full details: github.com/danveloper/f... #localinference #ai #llms #ml #macbook #apple
Very interesting: "Pure C/Metal inference engine that runs Qwen3.5-397B-A17B (a 397 billion parameter Mixture-of-Experts model) on a MacBook Pro with 48GB RAM at 4.4+ tokens/second with production-quality output including tool calling." #localinference #llms #ai #ml #macs
github.com/danveloper/f...
github.com/danveloper/f...
GitHub - danveloper/flash-moe: Running a big model on a small laptop
Running a big model on a small laptop. Contribute to danveloper/flash-moe development by creating an account on GitHub.
github.com
March 22, 2026 at 6:31 PM
Very interesting: "Pure C/Metal inference engine that runs Qwen3.5-397B-A17B (a 397 billion parameter Mixture-of-Experts model) on a MacBook Pro with 48GB RAM at 4.4+ tokens/second with production-quality output including tool calling." #localinference #llms #ai #ml #macs
github.com/danveloper/f...
github.com/danveloper/f...
But tab complete? That has to be local. Sometimes the right architecture is admitting which workloads cannot tolerate a network hop. #selfhosting #localinference #latency #localai #aiarchitecture 3/3
July 15, 2026 at 4:40 PM
But tab complete? That has to be local. Sometimes the right architecture is admitting which workloads cannot tolerate a network hop. #selfhosting #localinference #latency #localai #aiarchitecture 3/3
When everything agrees on one format, switching costs drop to nearly zero. #selfhosting #localinference #openaicompatible #localllm #localmodels 3/3
July 14, 2026 at 8:15 PM
When everything agrees on one format, switching costs drop to nearly zero. #selfhosting #localinference #openaicompatible #localllm #localmodels 3/3
Quantizing to 4-bit brings a 7B model down to a little over 4 GB. #gpuoptimization #gpuoptimization #quantization #llm #vram #localinference 2/2
June 8, 2026 at 12:32 AM
Quantizing to 4-bit brings a 7B model down to a little over 4 GB. #gpuoptimization #gpuoptimization #quantization #llm #vram #localinference 2/2
Just ran setup_env.py and it compiled the BitNet‑b1.58‑2B‑4T C++ backend with CMake in seconds. Ready for local inference on your machine—no Hugging Face hassle. Dive into the details! #BitNet #PythonCMake #LocalInference
🔗 aidailypost.com/news/python-...
🔗 aidailypost.com/news/python-...
March 10, 2026 at 4:32 PM
Just ran setup_env.py and it compiled the BitNet‑b1.58‑2B‑4T C++ backend with CMake in seconds. Ready for local inference on your machine—no Hugging Face hassle. Dive into the details! #BitNet #PythonCMake #LocalInference
🔗 aidailypost.com/news/python-...
🔗 aidailypost.com/news/python-...
Run massive AI locally! Deploy high-parameter models (100B–250B) using low-bit quantization like Q1 or Q2. This strategy allows you to fit huge weights on consumer hardware by optimizing local inference and memory efficiency. #AI #LLM #MachineLearning #LocalInference #Quantization
July 17, 2026 at 9:07 PM
Run massive AI locally! Deploy high-parameter models (100B–250B) using low-bit quantization like Q1 or Q2. This strategy allows you to fit huge weights on consumer hardware by optimizing local inference and memory efficiency. #AI #LLM #MachineLearning #LocalInference #Quantization
Configuring local inference in Xcode: how I set up Xcode, OpenCode, LM Studio and Gemma 4 for local, agentic software development through the Coding Assistant UI.
www.patreon.com/chironcodex/...
#Xcode #localai #lmstudio #localinference
www.patreon.com/chironcodex/...
#Xcode #localai #lmstudio #localinference
August 11, 2026 at 7:28 PM
Configuring local inference in Xcode: how I set up Xcode, OpenCode, LM Studio and Gemma 4 for local, agentic software development through the Coding Assistant UI.
www.patreon.com/chironcodex/...
#Xcode #localai #lmstudio #localinference
www.patreon.com/chironcodex/...
#Xcode #localai #lmstudio #localinference
Besoin de retranscrire du contenu audio ou vidéo 100 % en local ? 🎙️⚡
Découvre whisper.cpp dans ma dernière vidéo !
➡️ youtu.be/4y5wyLK8xjI
#OpenSource #AI #Whisper #Tech #LocalInference
(Vidéo réuploadée suite bug youtube)
Découvre whisper.cpp dans ma dernière vidéo !
➡️ youtu.be/4y5wyLK8xjI
#OpenSource #AI #Whisper #Tech #LocalInference
(Vidéo réuploadée suite bug youtube)
August 1, 2026 at 5:31 AM
Besoin de retranscrire du contenu audio ou vidéo 100 % en local ? 🎙️⚡
Découvre whisper.cpp dans ma dernière vidéo !
➡️ youtu.be/4y5wyLK8xjI
#OpenSource #AI #Whisper #Tech #LocalInference
(Vidéo réuploadée suite bug youtube)
Découvre whisper.cpp dans ma dernière vidéo !
➡️ youtu.be/4y5wyLK8xjI
#OpenSource #AI #Whisper #Tech #LocalInference
(Vidéo réuploadée suite bug youtube)
Image generation quality has exploded, but running it locally is still messy — especially for Java developers and ARM hardware.
A hands-on guide on embedding a native image model directly into the JVM using #Quarkus and the #Java #FFM API.
buff.ly/9t29far
#LocalInference #AIEngineering
A hands-on guide on embedding a native image model directly into the JVM using #Quarkus and the #Java #FFM API.
buff.ly/9t29far
#LocalInference #AIEngineering
February 15, 2026 at 8:25 AM
Image generation quality has exploded, but running it locally is still messy — especially for Java developers and ARM hardware.
A hands-on guide on embedding a native image model directly into the JVM using #Quarkus and the #Java #FFM API.
buff.ly/9t29far
#LocalInference #AIEngineering
A hands-on guide on embedding a native image model directly into the JVM using #Quarkus and the #Java #FFM API.
buff.ly/9t29far
#LocalInference #AIEngineering