docs: initial Gemma 4 research corpus and synthesis

Architecture specs, benchmarks, gotchas, Ollama settings, tool calling
format, and implementation patterns from Simon and AI_Visualizer.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

CORPUS_capabilities.md

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+# Gemma 4 Capabilities Reference
+
+## Modalities
+
+### Text (all variants)
+- Standard instruction-following, chat, completion
+- System prompt support (critical — see synthesis)
+- 128K context window (training length)
+- 262K vocabulary
+
+### Vision (all variants)
+- **Tested and verified working** (Seth, 2026-04-10)
+- Accurately described colors, shapes, composition in 256x256 test image
+- ~25 tok/s, ~24s end-to-end on pve197 V100
+- Input: base64-encoded image in `images` field of Ollama API
+- Vision encoder: 16x16 patches, 2D RoPE, variable aspect ratio
+- Token budgets scale with resolution (70-1120 soft tokens)
+- Used in AI_Visualizer for SDXL frame quality criticism
+
+### Audio (E2B/E4B only)
+- **Not tested by Seth** — status unknown in practice
+- Conformer architecture (~300M params), mel-spectrogram input
+- **Trained on SPEECH ONLY — not music or environmental sounds**
+- Maximum 30 seconds per clip
+- NOT available on 26B or 31B variants
+- AI_Visualizer explicitly rejected audio for music analysis (DECISIONS S2) — correct call, model wasn't trained for it
+
+### Video (all variants)
+- E2B/E4B: video WITH audio (`load_audio_from_video=True`)
+- 31B/26B: video WITHOUT audio
+- Not explicitly post-trained on video but works
+- Maximum 60 seconds at 1 frame/second
+- Not tested by Seth
+
+### Tool Calling / Function Calling
+- **Verified reliable** in both Simon and AI_Visualizer
+- Ollama native tool format (OpenAI-compatible function calling)
+- Simon: 6 genealogy tools, up to 12 sequential iterations
+- Supports parallel tool calls in single response
+- Weak at deeply nested JSON schemas -> prefer sequential calls
+
+## Benchmark Context (vs Gemma 3)
+
+- 31B replaces Gemma 3 27B (60 layers vs 62, but wider)
+- MoE variant (26B) is new — no Gemma 3 equivalent
+- E-series with PLE is new — on-device focus
+- Proportional RoPE replaces linear frequency scaling -> better long-context
+- Shared KV cache is new -> more efficient inference
+
+## What Gemma 4 Does NOT Do
+
+- No native code execution / sandboxing
+- No web browsing or retrieval
+- Audio only on E-series (not the models most people run)
+- No built-in RAG — tool calling can implement it