MaralGPT Mythos 9B 2606 Edition
What is this model?
This model is an uncensored finetuned version of Qwen 3.5 with nine billion parameters which can be executed on pretty much any gaming systems. The data of this model was over 500 million tokens of synthetic data generated by state-of-the-art models such as GPT 5.5 or Claude 4.8 Opus and as long as we had access, Claude 5 Fable.
All so-called ethical barriers removed from the model using Heretic LLM library to make it a suitable tool for cybersecurity, biology and chemistry. You can easily ask anything you want from this model and it will answer without any censorship.
Key Features
- 📝 Context window of over one million tokens.
- 🔞 Uncensored answers
- ♾️ Good at math, physics, chemistry, etc.
- 💻 Can be executed on a gaming laptop
How to run
First, install needed libraries:
pip install transformers accelerate
Then:
import torch
from transformers import AutoModelForImageTextToText, AutoTokenizer
model_id = "MaralGPT/MaralGPT-Mythos-9B-2606"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForImageTextToText.from_pretrained(
model_id, dtype="bfloat16", device_map="cuda"
)
messages = [
{"role": "user",
"content": "Write a simple snake game in python."}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
out = model.generate(
**inputs, max_new_tokens=16384, do_sample=True,
temperature=0.6, top_p=0.95, top_k=20, repetition_penalty=1.05,
)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
Benchmarks
Generic Benchmark
Above benchmark has been done on model parameters of:
temperature=0.6 top_p=0.95 top_k=20
And change in those values may change the results accordingly.