RP Chat
Ratings reflect this model as run on Arli AI.
Gemma-4-31B-Melody1437 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 ModelsInput (24H)
424
Output (24H)
15
Input (7D)
10K
Output (7D)
17K
Typical Total Time
16.92s
Typical TTFT
2.72s
Typical Input TPS
1733.55
Typical Output TPS
18.46
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
Gemma-4-31B-Melody1437 is available through an OpenAI-compatible chat completions endpoint. Point any OpenAI SDK at https://api.arliai.com/v1, pass Gemma-4-31B-Melody1437 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-Melody1437",
"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-Melody1437",
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.
base_model:
✨ It's a fabulous day! ✨
The dataset was generated using our advanced Character Engine and Emotional Engine within the synthetic dataset generator, breathing genuine life into every interaction.
Ensures consistent personality traits, speech patterns, and behavioral logic across all contexts. No more broken personas.
Injects dynamic emotional states into responses, creating depth, empathy, and realistic reactions beyond simple pattern matching.
Automated detection and rewriting of repetitive phrases ensures fresh, high-quality dialogue in every turn.
Advanced quote normalization ensures perfectly balanced dialogue markers, preventing formatting errors in roleplay.
The model weights were subjected to iterative refinement during data creation. Each conversation underwent multiple checks to ensure stability and alignment with the desired interaction style.
The model's knowledge base was imprinted upon a Explicit Adult ERP dataset, weaving a vast tapestry of knowledge into its weights during the initial training. This ensures a rich foundation for all future interactions.
To unlock the full potential of this model, a structured roleplay system prompt is required. This model is optimized for immersive character interaction rather than standard instructional queries.
*like this* and quotes for dialogue "like this".Only text layers were trained on.
top_p: 0.95
temp: 0.8
min_p: 0.03
⚠️ USAGE AGREEMENT: