8436a91571984d26993062a3a1c8f3028c8bb590
Seth's challenge: "we experienced this context eating with every implementation that had think=true. mort-bot runs a loop. Can you do a bake-off?" Built a harness that replicates mort-bot's /api/chat loop verbatim (num_ctx=8192, num_predict=2048, temperature=0.7, gemma4:26b, STEP_BUDGET=20, exact payload shape) but with stubbed tools and a prebuilt 15-turn fake chat history. Ran 4 tasks × 2 think settings. Finding: on Ollama 0.20.4 the "thinking eats context" concern does NOT reproduce. Direct evidence: - Movies task step 2 (think=true) returned 905 chars of thinking. - Step 3 prompt_eval_count delta: +76 tokens (think=true) vs +135 tokens (think=false). If thinking had accumulated in the prompt, think=true would have grown by +360 tokens, not shrunk. - Ollama's chat template strips the `thinking` field when serializing assistant turns for subsequent prompts. All 4 tasks × 2 settings produced identical step counts and tool counts. Wall clocks comparable. Gemma only actually generated thinking on 1 of 4 tasks (the one with check_sethflix verify-loop); on the others with think=true it emitted 0 thinking tokens. Reconciled with the earlier coding-agent bakeoff: the two findings are orthogonal. Coding bakeoff was at num_ctx=32K with a different harness; mort at 8K doesn't touch the silent-stop regime either way. Seth's prior may have been correct on an older Ollama or in a different API shape (/api/generate has its own issues) but does not reproduce here. Concrete recommendation: mort-bot THINK=False is defensible but not load-bearing; THINK=True or unset-default would also work. Keep as-is unless a different need arises. New: docs/reference/mort-bakeoff-2026-04-18.md, scripts/mort-bakeoff/ (harness + 8 run logs). README updated with pointer.
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 |
CLI-coding-agent bakeoff on 3090 Ti. Rounds 1/2 misidentified the cause; Round 3 (the correct one): think: false silent-stops gemma4:26b at certain multi-turn states on 32K context. 31B and Qwen3-Coder robust to the flag. Harness at scripts/bakeoff/ |
When deciding which model to back a CLI agent with, writing a custom agent payload, or debugging a silent tool-call halt |
docs/reference/mort-bakeoff-2026-04-18.md |
mort-bot-specific think=true vs think=false bakeoff on mort's actual loop shape (gemma4:26b, num_ctx=8192). Thinking does NOT accumulate in context on Ollama 0.20.4 — strips it from serialized history. Both settings behave identically on step counts, tool counts, wall clock. Harness at scripts/mort-bakeoff/ |
When deciding mort-bot's THINK env var, or when someone claims "think=true eats context" without pinning an Ollama version |
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.
Description
Languages
Jupyter Notebook
79.5%
HTML
12.5%
Python
7.5%
Jinja
0.4%