Jan-Code-4B: A Lightweight Code-Tuned Model for Local Development
Jan-Code-4B Release Details
The Jan team has released Jan-Code-4B, a small code-tuned model built on Jan-v3-4B-base-instruct. This experimental model targets day-to-day coding assistance tasks including code generation, edits/refactors, basic debugging, and writing tests while maintaining a lightweight footprint suitable for local execution.
Intended Use and Performance
Jan-Code-4B is designed as a drop-in replacement for the Haiku model in Claude Code. On coding benchmarks, it shows small improvements over the baseline model and generally feels more reliable for coding-oriented prompts at this size.
How to Run Jan-Code-4B
Setup via Jan Desktop:
- Download Jan Desktop from https://www.jan.ai/
- Download Jan-Code via Jan Hub
Claude Code Integration:
- Jan makes it easier to connect Claude Code to any model
- Replace Haiku model with Jan-Code-4B
Model Links and Parameters
Model downloads:
- Jan-Code: https://huggingface.co/janhq/Jan-code-4b
- Jan-Code-GGUF: https://huggingface.co/janhq/Jan-code-4b-gguf
Recommended parameters:
- Temperature: 0.7
- Top_p: 0.8
- Top_k: 20
The Jan team credits u/Alibaba_Qwen for the base model and u/ggerganov for llama.cpp contributions.
📖 Read the full source: r/LocalLLaMA
👀 See Also
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Claude Code Plugin Yoink Replaces Library Dependencies to Reduce Supply Chain Risk
Yoink is a Claude Code plugin that removes complex dependencies by reimplementing only needed functions, using a three-step workflow with /setup, /curate-tests, and /decompose commands. It currently supports Python with TypeScript and Rust support underway.
Unsloth Studio enables 2x training speed with 70% VRAM reduction for local AI fine-tuning
Unsloth Studio provides tools to train and fine-tune language models on local hardware with 2x faster training and 70% VRAM reduction. It supports exporting models to GGUF format for use with Ollama and enables full local AI coding workflows on 24GB hardware like RTX 4090.