Coding

What is it?

Coding models are explicitly trained or tagged for software tasks: code generation, refactoring, bug fixing, repository-level reasoning. They are normal GGUF chat models with code-heavy training data.

When should I use one?

• Backend for coding assistants (Integrations) — OpenCode, Cline, Continue.
• Terminal-first workflows via CLI chat.
• Scripted automation through the local API.

Prerequisites

• A model tagged for code tasks — filter the catalog by Coding.
• Enough memory: capable coding models are typically 7B+; 14B+ is meaningfully better.
• For agentic tools: a model with tool-calling support — Tool use.

Minimal working example

botconnector models search coder --capability coding
botconnector get <publisher>/<model>@Q4_K_M
botconnector run <publisher>/<model>

Then point your editor tool at the local endpoint:

http://127.0.0.1:11435/v1

Config examples per tool: Integrations.

Choosing size vs speed

A smaller model that responds quickly often beats a large model that thrashes memory. See Context and memory.

Limitations

• Context length decides how much code fits in one request — see the model's context length on its detail page.
• Agentic coding tools need tool-calling; text-only models answer once and cannot call tools.
• Long files exceed context; split or use a larger-context model.

Troubleshooting

Wrong language, broken syntax, forgotten instructions: Model problems.