# gemma4-research

Research corpus and implementation guidance for Google Gemma 4, based on production use in Seth's homelab.

## Files

| File | What | When to Read |
|------|------|-------------|
| `SYNTHESIS.md` | **Start here.** Opinionated guide — how to build with Gemma 4 | Before any new Gemma 4 implementation |
| `GOTCHAS.md` | Known issues and workarounds, severity-ranked | When debugging Gemma 4 issues or starting a new project |
| `IMPLEMENTATIONS.md` | Patterns from Simon and AI_Visualizer | When designing a new Gemma 4 integration |
| `CORPUS_architecture.md` | Model architecture details (layers, attention, PLE, MoE) | When you need to understand WHY Gemma 4 behaves a certain way |
| `CORPUS_ollama_variants.md` | Available models, sizes, VRAM, Ollama settings | When choosing a model variant or configuring Ollama |
| `CORPUS_capabilities.md` | Modalities (vision, audio, video, tools), what it can/can't do | When scoping what Gemma 4 can handle |
| `CORPUS_benchmarks.md` | Full benchmark table vs Gemma 3, arena scores, agentic scores | When comparing Gemma 4 to alternatives |
| `CORPUS_tool_calling_format.md` | Native token format + JSON API format for function calling | When implementing tool calling |
| `CORPUS_cli_coding_agent.md` | Positioning Gemma 4 for CLI coding agent use (openclaw / open code / pi / hermes / aider style). Honest take on what Google did and didn't measure, head-to-head with `qwen3-coder:30b`, homelab setup pointer | When scoping a CLI coding agent or deciding Gemma 4 vs Qwen3-Coder |
| `docs/reference/bakeoff-2026-04-18.md` | Raw results: CLI-coding-agent bakeoff of gemma4:26b / gemma4:31b / qwen3-coder:30b on steel141 3090 Ti. **31B clean, Qwen3-Coder correct but chatty, 26B reproducibly silent-stops at write_file.** Harness at `scripts/bakeoff/` | When deciding which model to back a CLI agent with, or debugging a similar tool-call halt |
| `tooling/` | **Canonical upstream tooling** — real scripts, notebooks, model cards, and configs pulled from Google / HF / framework maintainers (147 files). Subdirs: `google-official/`, `huggingface/`, `inference-frameworks/`, `gemma-family/`, `fine-tuning/`. See `tooling/README.md` for index and findings that update the older `CORPUS_*` docs | When you need authoritative source material — model cards, chat templates, fine-tuning recipes, serving commands for vLLM / llama.cpp / MLX, or to scope a specialized sibling (ShieldGemma, EmbeddingGemma, etc.) |

## Source Projects

- **Simon** (`~/bin/FreibergFamily/simon/`) — Multi-turn chat agent with 6 tools, genealogy historian
- **AI Visualizer** (`~/bin/AI_Visualizer/`) — Music video generator, 4-stage Gemma pipeline + vision

## Key Insight

Gemma 4 is ultra-compliant and highly capable but doesn't know who it is. It needs explicit system prompts, not hand-holding. Due to fast local inference, sequential tool calls beat long JSON requests.