#Large Language Models

Vram For Llm Memory ChartAI

VRAM for Local LLMs: How Much Each Model Size Needs at Every Quantization Level

A reference chart of memory needs for 8B to 70B models at Q4, Q8, and FP16, plus context overhead, Apple Silicon limits, GPU fit, and a formula.

Waqas Ahmad•
Illustration of a desktop computer and a laptop each with a glowing chip above itAI

How to Run an LLM Locally With Ollama: Setup for Windows, Mac, and Linux

Ollama runs open models on Windows, macOS, and Linux. Hardware needs by model size, install steps, a first chat, and the local API on port 11434.

Waqas Ahmad•
Comparing JSON and TOON structured data formats for reducing token use in AI promptsAI

JSON vs TOON: Token Usage, Cost, and Key Differences

JSON vs TOON explained: compare token usage, API cost, accuracy, and compatibility, then learn when TOON is worth testing for LLM prompts.

Waqas Ahmad•
Flat illustration of an AI model connected to tools, context, and a feedback loop by an agent harnessAI

What Is an AI Agent Harness? How It Works and Why It Matters

An AI agent harness connects a model to tools, context, execution, and safety controls. Here is how it works and why reliable agents need it.

Waqas Ahmad•
Mistral Large 4 represented as a large open-weight AI model connecting France with global AI benchmarks and cloud infrastructureAI

Mistral Large 4 Makes France a Serious AI Contender Again - But There's a Catch

Mistral Large 4 reaches 38 on Artificial Analysis, putting France's model at the top outside the U.S. and China while its task cost remains high.

Waqas Ahmad•
Showing OpenAI's AI models connected to ChatGPT, APIs, agents, Codex, tools, voice, images, and appsAI

What Does OpenAI Do? A Complete Guide to ChatGPT, Models, APIs, Agents, and Codex

What Does OpenAI Do? This guide explains how OpenAI's models, ChatGPT, APIs, agents, Codex, tools, voice, images, and apps fit together for readers.

Waqas Ahmad•
Gemini 4 Argon represented as a large AI model processing long streams of code and dataAI

Google Launches Gemini 4 Argon With a 1 Million-Token Output Limit

Gemini 4 Argon raises Google’s output limit from 64K to 1 million tokens for long coding, enterprise, and cybersecurity workflows in its first rollout.

Saganote•
Illustration showing a developer workflow for using Jev AI to turn application state into typed decisionsAI

How to Use Jev AI: A Practical Guide for Developers and AI Agents

Learn how to use Jev AI in a real application, from defining a decision and preparing state to calling the API and handling structured results safely.

Saganote•
What Is Jev AiAI

What Is Jev AI? How TypeSafe’s System One Decision Model Works

Learn what Jev AI is, how TypeSafe’s System One model works, and how typed decisions differ from generative LLM outputs in AI applications today.

Saganote•
Editorial illustration comparing token-by-token LLM generation with a decision model that routes one input into structured outcomesAI

Why Decision Models Like Jev Can Be Much Faster Than LLMs

Decision models answer bounded software questions without generating text. Jev shows how that can reduce latency and simplify routing, scoring, and triage.

Saganote•
Editorial illustration of an AI data agent turning business questions into interactive Power BI and Tableau dashboards.AI

OpenAI's Data Agent Turns Questions Into Power BI and Tableau Dashboards

OpenAI's new Data agent in ChatGPT Work can analyze connected company data and build dashboards in Power BI, Tableau, and other BI tools.

Saganote•
DeepSeek V4.1 Flash processing text and image inputs through a multimodal AI architectureAI

DeepSeek V4.1 Flash Launches With Native Vision and Lower AI Inference Costs

DeepSeek V4.1 Flash brings native visual understanding, a 552B MoE architecture, lower cache overhead, and new API pricing.

Saganote•