18 posts found
Askimo's new built-in Local LLM provider downloads a platform-matching llama-server binary and lets you browse, search, and download GGUF chat and embedding models straight from Hugging Face. One toggle, one model picker, zero extra installs: Ollama and LM Studio become optional, not required.
A deep dive into Voice in Askimo Desktop: dictate with OpenAI Whisper or a fully in-process whisper.cpp engine with live captions, and have responses read back via OpenAI, Piper, or your OS's own text-to-speech - mix and match for a setup that's cloud-quality or fully offline.
Askimo 1.5.4 brings local LLM engine support and full voice capabilities powered by Whisper - live transcription, text-to-speech, and cancellable downloads - plus smarter inline suggestions and a round of desktop reliability fixes.
Askimo 1.5 adds Agents: a single interface for running Claude Code, Antigravity CLI, or Codex CLI directly against your local project files - reading, writing, and executing with your review. Reusable Skills, GitHub and ZIP imports, and autonomous skill selection mean you describe a goal once and Askimo figures out which capability applies. Here is how it works and how it fits alongside Askimo Plans.
The best MCP clients in 2026 compared: Askimo Desktop, Claude Desktop, Open WebUI, LibreChat, AnythingLLM, and Msty. MCP (Model Context Protocol) lets AI use real tools - GitHub, databases, local files, web search. This guide covers which chat client fits your workflow, what MCP features each supports, and how to get started in minutes.
MCP and function calling both let an AI use tools. But function calling is a per-request contract you define in code, while MCP is a persistent protocol that exposes tools from a running server. This guide explains the difference clearly, when each approach makes sense, and how tools like Askimo Desktop let you use both without writing any code.
Askimo 1.4.8 gives you direct control over AI reasoning quality with configurable Reasoning Effort levels and per-model support. Anthropic prompt caching speeds up repeated queries, while drag-and-drop file attachments make it easier to share context. New font settings, accent color palettes, and spacing improvements create a more polished and personalized interface. Token usage tracking and a system diagnostics dialog improve visibility into how Askimo is running.
Compare top 5 Gemini desktop clients for 2026. Askimo excels with native performance, multiple AI models support, RAG-powered project indexing, AI Plans for multi-step workflows, and Agent Skills backed by Gemini CLI, Claude Code, and Codex CLI. Google AI Studio offers official integration. Msty provides multi-provider desktop chat. BoltAI delivers Mac-native AI assistance. Chatbox offers minimal, lightweight chat. All support Gemini but differ in features, privacy, and multimodal capabilities. Includes setup guides and use-case recommendations.
AI agents are powerful when the path to an answer is unknown. But for repeatable AI workflow automation - a research report, a code review, a competitive brief - agents fail in practice due to non-deterministic output, retry loops, and unpredictable costs. This post explains the difference between agents and deterministic AI Plans, when to use each, and why Plans are the better default for structured professional work.
A generic resume gets ignored. Recruiters and ATS systems filter for exact keyword matches, role-specific language, and tailored experience framing. This guide shows how to use Askimo Plans as your AI resume tailor, automatically analysing a job post, mapping it to your experience, rewriting the relevant sections, and producing a customized resume ready to submit. No prompt engineering required.
MCP (Model Context Protocol) lets your AI do real things, not just answer questions. Connect Askimo Desktop to GitHub, databases, local files, web search, and any API via Stdio or HTTP. Secrets stay in your OS keychain. Works with Claude, GPT, Gemini, and local Ollama models.
Askimo's Script Runner makes AI-generated code actually useful. Run Python, Bash, or Node.js scripts directly inside the app, view real stdout output instantly, and iterate faster without copy-pasting into a terminal. Great for data processing, log analysis, small automations, and reproducible workflows - all local, all private.
New in Askimo: built-in terminal emulator, Model Context Protocol (MCP) integration, a RAG sources tree to inspect exactly what the assistant used, image-model support for multimodal workflows, and major desktop improvements across performance, reliability, and UX.
The best AI desktop app isn't the one with the best single model - it's the one that lets you use ChatGPT, Claude, Gemini, and Ollama together. Switch models mid-conversation, keep sensitive data local, and cut API costs by routing simple tasks to free local models. Askimo is free, open source, and works on macOS, Windows, and Linux.
Askimo 1.2.0 introduces project-based RAG for answering questions using your documents with jvector and Apache Lucene search. Attach PDFs, spreadsheets, images, or code directly in conversations. Docker AI support joins OpenAI, Claude, Gemini, and Ollama. Enhanced project sessions organize knowledge-based chats. Responsive design works across all screen sizes. macOS installer now fully notarized for secure installation.
Compare top 5 Ollama desktop clients for 2026. Askimo excels with native performance, multiple AI models support, and RAG-powered project indexing. LM Studio offers easy model management. Open WebUI provides self-hosted team workflows. AnythingLLM focuses on document RAG for chatting with PDFs. Chatbox delivers minimal, lightweight chat. All support local-first privacy but differ in performance, RAG capabilities, and features. Includes setup guides and use-case recommendations.
Major Askimo App update adds multilingual support for 10+ languages including English, Vietnamese, Chinese, Japanese, Korean, French, German, Spanish, Portuguese, and Italian. Introduces 18 themes with light, dark, and system-adaptive options. New developer tools include real-time resource monitoring, enhanced debugging, and granular log controls. Significant performance improvements especially on Windows, plus better error handling across all platforms.
Askimo originated from developer frustration with fragmented AI tools. Created as a unified CLI for OpenAI, Ollama, and other providers, it became a daily-use command-line assistant for summarizing documents, writing drafts, and development tasks. Works everywhere via Homebrew, binaries, or Docker. Supports local context for project questions and seamless provider switching. Emphasizes reusable prompts and command recipes for DevOps automation.
