G

Gemma-4-31B-GarnetV3

RP Chat

No ratings yet(0)
Prose
—(0)
Intelligence
—(0)
Knowledge
—(0)
Instruction Following
—(0)
Coding
—(0)
Steerability
—(0)
Sign in to vote

Ratings reflect this model as run on Arli AI.

Gemma-4-31B-GarnetV3 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)

121K

Output (24H)

15

Input (7D)

501K

Output (7D)

20K

Performance Metrics

Typical Total Time

17.29s

Typical TTFT

2.74s

Typical Input TPS

1728.17

Typical Output TPS

18.01

Model Information

Context Size

262144

Quantization

r128 on FP8

Engine

vllm

Creation Method

Finetune

Model Class

Gemma-4-31B - LoRA

Chat Template

Gemma4

Reasoning

Yes

Vision

Yes

Parameters

31B

Added At

9/26/2026

Use Gemma-4-31B-GarnetV3 with the Arli AI API

Gemma-4-31B-GarnetV3 is available through an OpenAI-compatible chat completions endpoint. Point any OpenAI SDK at https://api.arliai.com/v1, pass Gemma-4-31B-GarnetV3 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-GarnetV3",
    "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-GarnetV3",
    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 base_model: google/gemma-4-31B-it pipeline_tag: text-generation datasets:

  • ConicCat/Charcards_Context_Distill_Gemma4_26BV2
  • ConicCat/Charcards_Delta_Qwen3_5V2
  • ConicCat/Lamp_P_Preference

ConicCat/Gemma4-GarnetV3-31B

GarnetV3 is a finetune of Gemma 4 focused on improving roleplay and writing performance using DPO with an emphasis on prose quality and humanlike characters. The dataset consists of approximately 1/3rds writing and 2/3ds roleplay.

How to Get Started with the Model

I recommend grabbing the Q4_K_M gguf and using koboldcpp.

Training Details

Training was conducted on 1xA100 80GB for 9 hours.

Datasets

  • ConicCat/Lamp_P_Preference: Human revised vs AI writing to improve prose.
  • ConicCat/Charcards_Delta_Qwen3_5V2: Qwen3.5 27B vs Qwen3.5 2B using the AI2 delta tuning recipe for data generation.
  • ConicCat/Charcards_Context_Distill_Gemma4_26BV2: Gemma 4 26B with full context as chosen and missing context as rejected.