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Gemma-4-31B-Sphinsikus-Chronist-V2

RP Chat

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Ratings reflect this model as run on Arli AI.

Gemma-4-31B-Sphinsikus-Chronist-V2 is a text generation model available on Arli AI. It offers 31B parameters, 262K token context, reasoning support, vision input. Recommended use: RP Chat. Run it through the OpenAI-compatible chat completions API with unlimited requests and zero-log privacy.

View on Hugging FaceBack to Models

Hourly Usage

Token Usage

Input (24H)

481K

Output (24H)

2K

Input (7D)

3M

Output (7D)

22K

Performance Metrics

Typical Total Time

17.12s

Typical TTFT

2.67s

Typical Input TPS

1734.38

Typical Output TPS

18.33

Model Information

Context Size

262144

Quantization

r128 on FP8

Engine

vllm

Creation Method

Merge

Model Class

Gemma-4-31B - LoRA

Chat Template

Gemma4

Reasoning

Yes

Vision

Yes

Parameters

31B

Added At

9/26/2026

Use Gemma-4-31B-Sphinsikus-Chronist-V2 with the Arli AI API

Gemma-4-31B-Sphinsikus-Chronist-V2 is available through an OpenAI-compatible chat completions endpoint. Point any OpenAI SDK at https://api.arliai.com/v1, pass Gemma-4-31B-Sphinsikus-Chronist-V2 as the model, and requests are served without logging.

cURL

curl https://api.arliai.com/v1/chat/completions \
  -H "Authorization: Bearer $ARLIAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Gemma-4-31B-Sphinsikus-Chronist-V2",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Python

from openai import OpenAI

client = OpenAI(
    base_url="https://api.arliai.com/v1",
    api_key="YOUR_ARLIAI_API_KEY",
)

response = client.chat.completions.create(
    model="Gemma-4-31B-Sphinsikus-Chronist-V2",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

See the text generation docs for every parameter, or read the quick start guide to make your first request.

Similar models

license: apache-2.0 language:

  • en tags:
  • merge
  • mergekit
  • roleplay base_model:
  • Blazed-Forge/Gemma-4-Gemsicle-31B
  • MRockatansky/Gemma-4-31B-storymaxxed2
  • BirdToast/Gemma-4-31B-glimmer-rp-v0.1
  • LatitudeGames/Equinox-31B
  • Jackrong/Gemopus-4-31B-it
  • ReadyArt/gemma-4-31B-it-scotoma-2
by Ateron

⏳ 📜 Sphinsikus Chronist V2 📜 ⏳

Sphinsikus Chronist Art

This is a library of stories, ready to be told or written.

🐀 About the Model

This is an improvement of old Sphinsikus Chronist, by injecting Scotoma V2 into it. Model should write with less slop, and have more stability, without loosing adventure knowledge.

  • Primary Focus: Character adherence. Role-play. Long context stories.

🗣️ Prompt Format

Please refer to the original google/gemma-4-31b-it for the correct chat template.

<|turn>user
Hello<turn|>
<|turn>model
Hi there<turn|>
<|turn>user
How are you?<turn|>
<|turn>model

🐀 Merge Details

I used mergekit as always:

Phase 1: Mixing (dare_ties)

I often trying to look for new methods and lurking around how models can be mixed, what can be used in it. Thanks to Nimbz for some hints, I goes over proj filters and I think, make some progression.

dare_ties 
merge_method: dare_ties
base_model: F:\AI\Merge\Gemma-4-it
tokenizer_source: base
dtype: bfloat16
parameters:
  lambda: 1.0
models:
  - model: F:\AI\Merge\Gemma-4-Scotoma-V2
    parameters:
      density: [0.40, 0.40, 0.40, 0.50, 0.50]
      weight:
      - {filter: mlp.gate_proj, value: 0.4}
      - {filter: mlp.up_proj, value: 0.6}
      - {filter: mlp.down_proj, value: 0.4}            
      - {filter: self_attn.q_proj, value: 0.3}
      - {filter: self_attn.k_proj, value: 0.3}
      - {filter: self_attn.v_proj, value: 0.5}
      - {filter: self_attn.o_proj, value: 0.5}
      - value: [0.40, 0.40, 0.40, 0.50, 0.50]

  - model: F:\AI\Merge\Gemma-4-SphinsikusChronist
    parameters:
      density: [0.70, 0.70, 0.70, 0.70, 0.65]
      weight:
      - {filter: mlp.gate_proj, value: 0.6}
      - {filter: mlp.up_proj, value: 0.4}
      - {filter: mlp.down_proj, value: 0.6}
      - {filter: self_attn.q_proj, value: 0.7}
      - {filter: self_attn.k_proj, value: 0.7}
      - {filter: self_attn.v_proj, value: 0.5}
      - {filter: self_attn.o_proj, value: 0.5}
      - value: [0.60, 0.60, 0.60, 0.50, 0.50]

🤝 Special Thanks

  • Google DeepMind: For providing the base model.
  • The Open-Source Community: For cheering people that share my passion for AI and RP.
  • Mergekit Fork: Zerofata - For making merges possible.
  • AesSedai: This smart man, to deslopping goofy G4.
  • To Nimbz: This fella for giving advices and helping me to improve technical knowledge.