Dzluck / gemma4-e4b-claude-coder-GGUF

Gemma 4 Claude Coder — local model family

A family of custom models built on Gemma 4 (edge variants E2B and E4B), tuned to act as autonomous coding and administration agents . The models speak the Anthropic-compatible API, so they drive Claude Code fully locally — your code never leaves your machine and cloud token cost drops to zero.

Each model ships with a system prompt focused on real work inside a codebase: use tools instead of guessing, make minimal and precise code changes, return complete and runnable output, and verify after acting. Sampling follows Google's official Gemma 4 recommendation (temperature 1.0, top_k 64, top_p 0.95), with thinking mode enabled for better planning before a tool call.

The idea

The whole point of this family is to run Claude Code on small, popular, consumer-grade hardware . No datacenter GPU, no cloud bill — just an everyday Mac Mini (or similar 16 GB machine) acting as a fully local, agentic coding assistant. These models make that practical: light enough to fit, smart enough to drive real tool-calling agent loops.

In a time of RAM shortages and the big tech giants tightening usage limits and quotas , owning a capable agent that runs entirely on your own modest hardware stops being a hobby and becomes leverage: no rate limits, no surprise pricing, no dependency on someone else's quota.

Models in the family

What it's for

• Driving Claude Code locally ( ollama launch claude --model <name> ).
• Agentic code writing and editing with native function calling / tool use .
• Administration and devops tasks on a server (the admin variant).
• Full privacy and offline operation — no code sent to the cloud.

Context

• Coders (E2B / E4B): 64K tokens — matching Claude Code's recommendation (64K minimum).
• Admin (E4B): 32K tokens — a deliberate trade-off for 16 GB hardware that keeps the model entirely on the GPU.
• Base Gemma 4 E2B/E4B natively supports up to 128K, so context can be raised on stronger hardware.

Test hardware

The models were built and tested on:

• Mac Mini (Apple Silicon, M-series), 16 GB RAM, macOS 15.6
• Ollama 0.24 , GPU (Metal) inference

Measured performance (16 GB RAM)

All three passed an end-to-end test through Claude Code: real turns with tool calls and correct responses (HTTP 200 on /v1/messages ).

How they were made

These models were designed, built and tested with the help of Claude Opus 4.8 — the best coding model in the world. Their system prompts, parameter choices and context configuration draw directly on its knowledge. In other words: the world's best coding model prepared local models that take that work over right on your desk.

License

Apache 2.0 (inherited from the base Gemma 4).