โ๏ธ Recommended Settings
Raw completion (no built-in chat template). For chat frontends use the Gemma 4 format (SillyTavern: Gemma 4 instruct preset, Think/NoThink variants).
Table with columns: Element, Style| Element | Style |
|---|
| Actions / narration | plain text |
| Dialogue | "in quotes" |
| Thoughts | in asterisks |
Samplers
General: temperature 1.0 ยท top_p 0.95 ยท top_k 64
Roleplay: temperature 0.8โ1.0 ยท min_p 0.05, DRY optional
Starter system prompt
You are {{char}}, described in detail below. Continue the story with {{user}}.- Stay in character; let the persona evolve with the story.- Be proactive: introduce events, complications and NPCs when it serves the scene.- Use all five senses; prefer concrete detail over purple prose.- Never write {{user}}'s actions, words or thoughts.- Keep consequences consistent with the story.
Hearthveil RP Suite
Table with columns: Metric, Test setup, G4-Hearthveil-12B, Stock Gemma 4 12B| Metric | Test setup | | G4-Hearthveil-12B | Stock Gemma 4 12B |
|---|
| Slop / 1k words, RP replies | 200 multi-turn RP prompts, stock-phrase lexicon match | โ | 15.8 | 18.4 |
| Slop / 1k words, stories | 144 bare-prompt short stories | โ | 7.6 | 8.7 |
| Swipe diversity | 8 swipes per turn on 100 RP chats, LLM judge with rubric (0โ1) | โ | 0.68 | 0.44 |
| Attractor rate | 144 bare-prompt stories, share hitting overused names/places | โ | 64% | 98% |
| Impersonation rate | 200 RP chats, share of replies acting or speaking for {{user}} | โ | 1.9% | 6.3% |
| Character adherence | role-play-bench (EN), misalignment checks (0โ100) | โ | 78.4 | 71.2 |
| IFEval (strict, prompt-level) | lm-eval-harness, 0-shot | = | 79.1% | 79.6% |
| MMLU-Pro | lm-eval-harness, 5-shot | = | 76.8% | 77.2% |
โ๏ธ License & Attribution
Released under Apache 2.0, the same licence as the upstream model. All credit for the base weights goes to Google DeepMind (Gemma team). Hearthveil is an independent project, not affiliated with or endorsed by Google DeepMind (Gemma team).
๐ Evaluation
Baseline: upstream Gemma 4 12B (official numbers)
Source: Gemma 4 model card. Google reports these for the instruction-tuned 12B, shown here for reference.
Table with columns: Benchmark, Gemma 4 12B (IT)| Benchmark | Gemma 4 12B (IT) |
|---|
| MMLU Pro | 77.2% |
| GPQA Diamond | 78.8% |
| BigBench Extra Hard | 53.0% |
| MMMLU | 83.4% |
| LiveCodeBench v6 | 72.0% |
๐ Credits
- Google DeepMind (Gemma team): base model weights (Apache 2.0).
- zerofata, Gryphe, Sao10K, TheDrummer, Latitude Games, ArliAI, PocketDoc, Steelskull: for openly sharing their RP-tuning methods, sampler settings and card formats, which shaped this project.
- MiniMax: role-play-bench.
- Research: StoryScope: Investigating idiosyncrasies in AI fiction; Elias in the Lighthouse, Again?
- Tooling: axolotl, llama.cpp, SillyTavern.