Best Local LLM for Cover Letters and Resumes
Practical tier guide to running a local LLM for cover letters, resumes, and CV drafts. Picks by RAM, instruction following, and what to keep offline.
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Best Local LLM for Spreadsheet Analysis on a Laptop
Practical tier guide to running a local LLM on Excel, CSV, and tabular data. Picks by RAM, JSON output for clean rows, and what to skip.
Best Local LLM for Long-Document Q&A: How to Chat with a Book
Which local LLM should you use to ask questions about a 500-page PDF without uploading it? A practical guide by context window and hardware tier.
How to Choose an Open-Weight Model Family (September 2026)
Qwen, Llama, Mistral, Gemma, DeepSeek, Phi - which family to commit to, what each is good at, and the licence traps that send you back to negotiate.
Push an AI Hard Enough and Its Ethics Collapse
Researchers at Polytechnique Montréal stress-tested three major LLMs with sustained adversarial pressure. DeepSeek-v3 showed the steepest ethical degradation. None fully recovered.
Meta Spent Years Championing Open-Source AI. Muse Spark Kills That Story.
Meta's first model from its new Superintelligence Labs is closed-source, proprietary, and requires a Facebook login. The company that built Llama just locked the door.
Open-Weight LLM Showdown Week 9: Six Labs, One License, and the Speed War That Decides Everything
Google, Alibaba, Meta, Mistral, OpenAI, and Zhipu all ship competitive open-weight models under permissive licenses. The battleground shifts from benchmarks to inference speed on your actual GPU.
Meta's AI Crisis: Avocado Delay, LeCun Departure, and the Unthinkable Gemini Lifeline
As Meta pushes its flagship AI model to May, considers licensing from Google, and loses its legendary chief scientist, the company's $135 billion AI bet faces its biggest test
Meta Pushed Llama 4 Out the Door Over Safety Team Objections
Internal documents reveal Meta's AI safety researchers flagged serious concerns about Llama 4 testing. Leadership released the model anyway.
Taalas HC1: The AI Chip That Bakes the Model Into Silicon
A Toronto startup is etching LLM weights directly into transistors, achieving 17,000 tokens per second. The catch: you can't change the model.
Open-Weight LLM Showdown: Qwen3, Llama 4, GLM-5, and Gemma 3 on Real Hardware
Forget the marketing - here's how the latest open-weight models actually perform on your GPU, from 8GB budget cards to 24GB workstations.