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Gemma-4-31B-Novelist-Eclipse

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Ratings reflect this model as run on Arli AI.

Gemma-4-31B-Novelist-Eclipse 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)

687K

Output (24H)

3K

Input (7D)

3M

Output (7D)

32K

Performance Metrics

Typical Total Time

17.47s

Typical TTFT

2.79s

Typical Input TPS

1718.09

Typical Output TPS

16.88

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-Novelist-Eclipse with the Arli AI API

Gemma-4-31B-Novelist-Eclipse is available through an OpenAI-compatible chat completions endpoint. Point any OpenAI SDK at https://api.arliai.com/v1, pass Gemma-4-31B-Novelist-Eclipse 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-Novelist-Eclipse",
    "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-Novelist-Eclipse",
    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 tags:

  • merge
  • mergekit
  • roleplay model_creator: Ateron pipeline_tag: text-generation quantized_by: f16 language:
  • en base_model:
  • nbeerbower/Gemma4-Gutenberg-31B
  • bgg1996/Melinoe-Gemma4-31B-VL
  • BirdToast/Gemma-4-31B-glimmer-rp-v0.1
  • ConicCat/Gemma4-GarnetV2-31B
  • Jackrong/Gemopus-4-31B-it
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🌑 Novelist-Eclipse

Novelist-Eclipse AI Persona

"When the stories bleed out"

🚀 Overview

Novelist end up to be raw and experimental. So I crank it up with more models, infusing creativity and worked on stability. Also added lm_head on top with StyleTune.

🌌 Mergekit Configuration

Below is the exact mergekit_config.yml recipe used to synthesize this model:

Phase 1: The Prose (dare_ties)

I took Novelist idea about description focus and remade it, so at the end less slop survive.

dare_ties Recipe 1 
merge_method: dare_ties
base_model: F:\AI\Merge\Gemma-4-it
tokenizer_source: union
parameters:
  lambda: 1.0
dtype: bfloat16
models:
  - model: F:\AI\Merge\G4-Gutenberg
    parameters:
      density: [0.50, 0.50, 0.50, 0.40, 0.45]
      weight: [0.40, 0.40, 0.40, 0.40, 0.40]

  - model: F:\AI\Merge\Melinoe
    parameters:
      density: [0.30, 0.30, 0.30, 0.30, 0.35]
      weight: [0.30, 0.30, 0.30, 0.20, 0.40]

  - model: F:\AI\Merge\Glimmer
    parameters:
      density: [0.20, 0.20, 0.20, 0.30, 0.20]
      weight: [0.30, 0.30, 0.30, 0.40, 0.20]

Phase 2: The Lead (model_stock)

The first stage was fine, but lacks of consistency, so I glued it with using two smart models.

model_stock Recipe 2 
models:
  - model: F:\AI\Merge\NovelistX
  - model: F:\AI\Merge\GarnetV2
  - model: F:\AI\Merge\Gemopus
merge_method: model_stock
base_model: F:\AI\Merge\Gemma-4-it
dtype: bfloat16
tokenizer_source: base

🤝 Special Thanks

  • Google DeepMind: For providing the base model.
  • The Open-Source Community: Creators and all their fine-tuned models that were used in the merge.
  • Mergekit Fork: Zerofata - For making mergekit work.
  • To Nimbz: This cat for being a smart fella and assisting with advices.