Lamapi / next-12b

🚀 Next 12B (m200)

Türkiye's Advanced Vision-Language Model — High Performance, Multimodal, and Enterprise-Ready

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📖 Overview

Next 12B is a 12-billion parameter multimodal Vision-Language Model (VLM) based on Gemma 3 , fine-tuned to deliver exceptional performance in both text and image understanding. This is Türkiye's most advanced open-source vision-language model , designed for:

• Superior understanding and generation of text and image descriptions .
• Advanced reasoning and context-aware multimodal outputs.
• Professional-grade Turkish support with extensive multilingual capabilities.
• Enterprise-ready deployment with optimized quantization options.

This model is ideal for enterprises, researchers, and organizations who need a state-of-the-art multimodal AI capable of complex visual understanding, advanced reasoning, and creative generation .

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Next 12B sets new standards for medium-sized models across all major benchmarks.

Model	MMLU (5-shot) %	MMLU-Pro %	GSM8K %	MATH %
Next 12B Version m200	91.8	78.4	94.3	81.2
Next 4B preview Version s325	84.6	66.9	82.7	70.5
Qwen 2.5 14B	79.9	68.3	87.5	74.3
Llama 3.1 8B	73.0	62.4	80.6	51.9

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Next 12B approaches frontier model performance while maintaining efficiency.

Model	MMLU (5-shot) %	MMLU-Pro %	GSM8K %	MATH %
Next Z1 Version l294	97.3	94.2	97.7	93.2
Next 12B Version m200	91.8	78.4	94.3	81.2
GPT 4o	88.7	72.6	92.3	76.6
Claude Sonnet 4	~88.3	75.8	90.8	78.3

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🚀 Installation & Usage

Use with vision:

from transformers import AutoTokenizer, AutoModelForCausalLM, AutoProcessor
from PIL import Image
import torch

model_id = "Lamapi/next-12b"

model = AutoModelForCausalLM.from_pretrained(model_id)
processor = AutoProcessor.from_pretrained(model_id) # For vision.
tokenizer = AutoTokenizer.from_pretrained(model_id)

# Read image
image = Image.open("image.jpg")

# Create a message in chat format
messages = [
  {"role": "system","content": [{"type": "text", "text": "You are Next-X1, a smart and concise AI assistant trained by Lamapi. Always respond in the user's language. Proudly made in Turkey."}]},

  {
      "role": "user","content": [{"type": "image", "image": image},
      {"type": "text", "text": "Who is in this image?"}
    ]
  }
]

# Prepare input with Tokenizer
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = processor(text=prompt, images=[image], return_tensors="pt")

# Output from the model
output = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(output[0], skip_special_tokens=True))

Use without vision:

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "Lamapi/next-12b"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

# Chat message
messages = [
    {"role": "system", "content": "You are Next-X1, a smart and concise AI assistant trained by Lamapi. Always respond in the user's language. Proudly made in Turkey."},
    {"role": "user", "content": "Hello, how are you?"}
]

# Prepare input with Tokenizer
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt")

# Output from the model
output = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(output[0], skip_special_tokens=True))

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🎯 Goals

1. Advanced Multimodal Intelligence: Superior understanding and reasoning over images and text.
2. Enterprise-Grade Performance: High accuracy and reliability for production deployments.
3. Efficiency: Optimized for professional GPUs with flexible quantization options.
4. Accessibility: Open-source availability for research and commercial applications.
5. Cultural Excellence: Best-in-class Turkish language support while maintaining multilingual capabilities.

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✨ Key Features

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📐 Model Specifications

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💡 Performance Highlights

• MMLU Excellence: 91.8% on MMLU benchmark, demonstrating comprehensive knowledge across diverse domains
• Mathematical Prowess: 81.2% on MATH benchmark, excelling in complex mathematical reasoning
• Problem Solving: 94.3% on GSM8K, showcasing superior word problem solving capabilities
• Professional Reasoning: 78.4% on MMLU-Pro, handling advanced professional-level questions

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🎨 Use Cases

• Enterprise Content Generation: High-quality multilingual content creation
• Advanced Visual Analysis: Detailed image understanding and description
• Educational Applications: Complex tutoring and explanation systems
• Research Assistance: Literature review and data analysis
• Creative Writing: Story generation and creative content
• Technical Documentation: Code documentation and technical writing
• Customer Support: Multilingual customer service automation
• Data Extraction: Visual document processing and information extraction

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📄 License

This project is licensed under the MIT License — free to use, modify, and distribute for commercial and non-commercial purposes. Attribution is appreciated.

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📞 Contact & Support

• 📧 Email: [email protected]
• 🤗 HuggingFace: Lamapi

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Next 12B — Türkiye's most advanced vision-language AI , combining state-of-the-art multimodal understanding, superior reasoning, and enterprise-grade reliability .