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Last updated April 2026 — refreshed for current Cherry Studio v1.9.x and Ollama 0.22.x releases, current models (Llama 4, DeepSeek V4, Qwen 3, Gemma 4), and Ubuntu 24.04 LTS as the default target. This is a working setup guide for running large language models entirely on

Quick answer. Cherry Studio v1.9.6 + Ollama on Windows gives you a free, fully-offline local LLM stack. Install both, point Cherry Studio at http://localhost:11434, and pick models by RAM: 16 GB handles Qwen 3.5 8B; 32 GB runs Gemma 4 9B or DeepSeek V4 distills at

This comprehensive guide walks you through every step—from prerequisites to advanced features—ensuring a smooth and efficient setup of Cherry Studio and Ollama on macOS. * Cherry Studio is a cross-platform desktop application for interacting with various large language models (LLMs). It supports providers like OpenAI, Gemini, Anthropic, and local

Quick answer. On Ubuntu 22.04 through 25.04, install Cherry Studio 1.9.x via the official .deb from github.com/CherryHQ/cherry-studio for one-command setup and proper menu integration. Skip the AppImage on 24.04+ unless you install libfuse2t64, since Ubuntu now ships FUSE 3. Flatpak is the

Quick answer. Cherry Studio v1.9.4 is a free, open-source desktop client for Windows 10/11 that connects to 300+ LLM providers (OpenAI, Anthropic, Gemini, DeepSeek, Ollama) in one UI. Download the `CherryStudio-Setup-x64.exe` from the official site, run the installer, then add your provider API key. Setup is

Cherry Studio is a powerful, cross-platform AI productivity desktop client built for seamless interaction with a wide array of large language models (LLMs) and AI web services. Whether you're a developer, writer, researcher, or tech enthusiast, Cherry Studio provides a unified interface to supercharge your workflow on macOS,

YouTube videos often stretching into hours, viewers increasingly seek efficient ways to extract key insights without watching the entire content. AI-powered YouTube video summarizers have emerged as essential tools for students, professionals, researchers, and casual viewers alike. Below is a detailed exploration of the top 10 best AI YouTube video

As video content continues to dominate digital platforms, the demand for efficient ways to digest long-form videos has skyrocketed. AI video summarizers have emerged as essential tools for students, professionals, content creators, and anyone seeking to extract key insights quickly. Below is a detailed guide to the top 10 best

Claude 4, Anthropic’s most advanced AI model suite, has quickly become essential for developers seeking intelligent, context-aware code assistance. By integrating Claude 4 Opus and Sonnet into AI-powered code editors like Cursor and Windsurf, developers can significantly boost productivity, improve code quality, and automate workflows. This guide covers everything

Gemma 3n is a cutting-edge, privacy-first AI model designed to run efficiently on local devices. It brings advanced multimodal capabilities—including text, audio, image, and video understanding—directly to your desktop or server. This guide provides a comprehensive step-by-step walkthrough for installing and running Gemma 3n locally using the Ollama

Quick answer. Run Devstral 2 with Ollama using the official tags: ollama pull devstral-small-2 (24B, 68.0% SWE-bench Verified, fits a 24 GB RTX 4090 or 32 GB Mac at Q4_K_M) or ollama pull devstral-2 (123B, 72.2% SWE-bench Verified, needs 4×24 GB VRAM or a single

Devstral, Mistral AI’s cutting-edge agentic coding model, is redefining the boundaries of automated software engineering. Whether you’re a hobbyist developer, a seasoned enterprise engineer, or a research scientist, Devstral offers unprecedented capabilities that streamline and scale complex coding workflows. Want the full picture? Read our continuously-updated AI Coding

Quick answer. Gemma 4 (April 2026) supersedes Gemma 3 (March 2025) and the mobile-focused Gemma 3n (June 2025). Gemma 4 31B hits 89.2% on AIME and 66.4% on RULER@128K, against 20.8% and 13.5% for Gemma 3 27B. The 26B A4B MoE beats Gemma 3 27B

Google’s Gemma series represents a significant leap in open, efficient, and multimodal AI models. With the arrival of Gemma 3 1B and the newly announced Gemma 3n, developers and AI enthusiasts are presented with advanced tools optimized for everything from cloud to mobile. This article provides a thorough, in-depth

Last updated April 2026 — refreshed for current model/tool versions and Void's paused development status. Void AI paired with Ollama gives you a fully local, private AI coding environment on Ubuntu — no subscriptions, no cloud, no data leaving your machine. This guide walks through a complete setup, covers

AI-powered code editors are transforming how developers write, refactor, and understand code. Among the most popular commercial options is Cursor, but its closed-source nature and subscription fees have prompted the rise of open-source alternatives. Void is one such tool, designed as a privacy-first, flexible, and powerful AI coding IDE that

As AI-powered coding assistants become central to modern software development, developers are increasingly seeking tools that combine power, privacy, and flexibility. Proprietary solutions like Cursor and GitHub Copilot have led the way, but their reliance on cloud-based models and closed ecosystems raises concerns about data privacy, cost, and vendor lock-in.

Void Linux is a lightweight, systemd-free Linux distribution lauded for its speed, minimalism, and control. With the rise of local AI and Large Language Models (LLMs), tools like Ollama have made it easier for users to run advanced AI models on their own hardware. This guide provides a thorough walkthrough

Quick answer. Pick Cursor in 2026 — Cursor 3 with Composer 2.5 (May 18, 2026) hits 79.8 on SWE-bench Multilingual and 69.3 on Terminal-Bench 2.0, with active multi-agent UI and weekly updates. Void's development remains paused (last source change August 4, 2025); the v1.99

Prompt caching has emerged as a powerful strategy for reducing the operational costs and improving the efficiency of AI systems, especially those powered by large language models (LLMs) like OpenAI’s GPT, Anthropic’s Claude, and others. As AI adoption accelerates across industries, understanding how prompt caching works and how

Last updated April 2026 — refreshed for current model/tool versions and 2025 ecosystem benchmarks. DeepSeek Prover V2 7B is the most capable open-source formal theorem-proving model at the 7B parameter scale, purpose-built for generating verified proofs in Lean 4. Released in April 2025, it remains the reference deployment target for

Running DeepSeek Prover V2 7B on Windows involves several key steps—ranging from environment preparation to downloading and executing the model. This guide walks you through everything you need to install and run DeepSeek Prover V2 7B on a Windows system effectively. What Is DeepSeek Prover V2 7B? DeepSeek Prover

Last updated April 2026 — refreshed for current model/tool versions. DeepSeek Prover V2 7B is one of the most capable open-weight formal theorem-proving models you can run locally. Released in late April 2025, it targets Lean 4 proof generation and remains fully relevant in 2026 — both the 7B and the

Last updated April 2026 — refreshed for current package versions, transport guidance, and the official MCP spec (2025-03-26). The Model Context Protocol (MCP) has become the dominant standard for connecting AI models to external tools and services — growing from 2 million monthly SDK downloads at its November 2024 launch to 97