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Dzluck/gemma4-e2b-claude-coder-GGUF

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Model Card

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, topk 64, topp 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

Model	Base	Context	Purpose
gemma4-e2b-claude-coder	Gemma 4 E2B (eff. 2B / 5.1B with embeddings)	64K	Fast everyday coding agent — edits, autocomplete, short agent loops. Lightest on memory.
gemma4-e4b-claude-coder	Gemma 4 E4B (eff. 4B / 8B with embeddings)	64K	Stronger coding agent — better reasoning and tool use on larger tasks.
gemma4-e4b-claude-coder-admin	Gemma 4 E4B	32K	Administration and system tasks (scripts, shell, devops). Smaller context fits 100% in GPU for higher, stable throughput.

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)

Model	Placement	Speed	Tool calling
gemma4-e2b-claude-coder	100% GPU	~55 tok/s	✅ valid JSON
gemma4-e4b-claude-coder (64K)	39% GPU / 61% CPU	~27 tok/s (drops under load)	✅
gemma4-e4b-claude-coder-admin (32K)	100% GPU	~30 tok/s (stable)	✅

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).