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miniagent

Free

A terminal coding agent for local models. Runs your shell, edits files, searches and browses the web - driven by a model on your own machine.

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Overview

miniagent is a terminal coding agent designed for local models. It runs shell commands, edits files, searches and browses the web, and maintains work across long tasks, all driven by a model running on the user's own machine without an API key and with nothing leaving the computer. It was built and tuned against Spark-X2.5-4B in LM Studio on Windows 11, and it speaks the ordinary OpenAI-compatible API, so llama.cpp, Ollama, vLLM, SGLang or a remote endpoint work just as well. It also drives Qwen3.8-27B on a free Kaggle TPU, served by kaggle-tpu-lab/ in the repository. The agent runs on the user's PC using only the standard library, and includes benchmark tasks and checkers, settings for a local SearXNG for web search, and the model side on a free Kaggle TPU. Requirements include Windows 11 (Windows 10 works too), Python 3.8+ with no third-party packages, a local model server such as LM Studio, and optionally Docker for a local SearXNG. The agent can be pointed to different endpoints with flags or environment variables, and it supports profiles like Ternary Bonsai 2 27B. Web search is optional but recommended, using a local SearXNG to avoid rate limits. The Kaggle TPU integration allows running Qwen3.8-27B with vLLM on Kaggle's free TPU v5e-8, with the agent running locally and only the model on Kaggle.

Pricing

Free

Detailed plans have not been confirmed in our catalog. Check the official website for current limits and billing terms.

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Prices and limits may change. Confirm the currency, billing period, seat minimum and usage caps on the official website.

Use Cases

  • Developers use miniagent to run shell commands and edit files directly from the terminal.
  • Teams use miniagent to search and browse the web for information without leaving the local environment.
  • Users use miniagent to work with local models via an OpenAI-compatible API, such as llama.cpp, Ollama, vLLM, or SGLang.
  • Users use miniagent to drive Qwen3.8-27B on a free Kaggle TPU for model inference.
  • Teams use miniagent to run benchmark tasks and their checkers for evaluation.
  • Users use miniagent to perform web search reliably through a local SearXNG instance.
  • Developers use miniagent to run one-shot tasks or tasks from a file in a specified directory.

Features

Local model driven coding agent

Terminal based coding workflow

Executes shell commands

Edits local files

Searches and browses the web

Runs on Windows 11

Uses only Python standard library

Works without API keys

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