Smallcode – AI coding agent optimized for small LLMs
SmallCode is an AI coding agent designed for small language models with 7B-20B parameters. It optimizes performance on consumer hardware by intelligently managing context and tool calls. The architecture includes features like model escalation and a forgiving tool call parser to enhance usability.
- ▪SmallCode is built to work with local models, improving their efficiency and reliability.
- ▪It includes a modular architecture that supports various functionalities like tool scoring and session management.
- ▪The agent can escalate to stronger cloud models if local models fail, ensuring continuous operation.
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SmallCode 简体中文 | English AI coding agent optimized for small LLMs (≤20B parameters) SmallCode is a terminal-native coding agent designed from the ground up to extract useful work from local models (7B-20B) running on consumer hardware. While tools like OpenCode assume frontier models with 128k+ context and perfect tool calling, SmallCode compensates for the limitations of small models through intelligent architecture. Why SmallCode? OpenCode SmallCode Target Frontier models (Claude, GPT-4) 7B-20B local models Context Dumps everything Budget-managed, summarized Tool calling Assumes reliable JSON Forgiving multi-format parser Planning Single-shot TODO-file decomposed steps Editing Full file write Search-and-replace patch Privacy API calls to cloud Fully local, no network needed Quick Start…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.