itayinbarr/little-coder

Health v2 · maintenance only

Flags: young

Adoption not part of the score

2504 stars · 168 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

little-coder is a terminal coding agent built on the pi agent loop, tuned for small local language models like Qwen via Ollama or llama.cpp. It bundles pi extensions, skill files, and a Python benchmark harness, and ships as an npm-installable CLI that reads, edits, and runs code against your working tree offline.

Use cases

• run a coding agent on a small local LLM offline
• benchmark small models on aider polyglot and terminal-bench
• edit code in my repo with a local qwen model
• use a coding assistant without sending code to the cloud
• test scaffold-model fit for coding agents
• serve a 35B MoE model on an 8GB laptop GPU for coding

When to choose

• you want an offline, privacy-preserving coding agent powered by small local models
• you need to benchmark or evaluate small LLMs on coding tasks
• you have limited GPU/VRAM and want a tuned agent scaffold

When to avoid

• you need frontier-model quality and prefer cloud APIs
• you rely on globally installed pi extensions, which don't load by default
• you need a GUI-based coding assistant

Facets

cli-tool · maturity active

agent-framework llm-inference developer-tools cli benchmarking large-language-models developer-tools cli windows coding-agent local-llm ollama small-language-models tool-use terminal-bench aider-polyglot qwen benchmark-harness pi-extensions ai-agents command-line nodejs macos linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="itayinbarr/little-coder")