thelamapi/next-12b

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🚀 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.

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

<table> <thead> <tr> <th>Model</th> <th>MMLU (5-shot) %</th> <th>MMLU-Pro %</th> <th>GSM8K %</th> <th>MATH %</th> </tr> </thead> <tbody> <tr> <td>Next 14B (Thinking)</td> <td><strong>94.6</strong></td> <td><strong>93.2</strong></td> <td><strong>98.8</strong></td> <td>92.7</td> </tr> <tr> <td><strong>Next 12B</strong></td> <td>92.7</td> <td>84.4</td> <td>95.3</td> <td>87.2</td> </tr> <tr class="next"> <td>Next 8B (Thinking)</td> <td>91.0</td> <td>88.5</td> <td>96.2</td> <td>88.0</td> </tr> <tr> <td>GPT-5</td> <td>92.5</td> <td>87.0</td> <td>98.4</td> <td><strong>96.0</strong></td> </tr> <tr> <td>Claude Opus 4.1 (Thinking)</td> <td>~92.0</td> <td>87.8</td> <td>84.7</td> <td>95.4</td> </tr> </tbody> </table> ---

🚀 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))

<div style='width:700px;'> <img src='/Lamapi/next-12b/resolve/main/assets/image.jpg' style='height:192px;border-radius:16px;margin-left:225px;'> <div style='background-color:rgba(0,140,255,0.5);border-radius:16px;border-bottom-right-radius:0px;padding:3px 10px;width:fit-content;max-width:400px;margin-left:250px;margin-top:-25px;margin-bottom:10px;'> Who is in this image? </div> <div style='background-color:rgba(42,42,40,0.7);border-radius:16px;border-bottom-left-radius:0px;padding:3px 10px;width:fit-content;max-width:400px;'> The image shows <strong>Mustafa Kemal Atatürk</strong>, the founder and first President of the Republic of Turkey. </div> </div>

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))

<div style='width:700px;'> <div style='background-color:rgba(0,140,255,0.5);border-radius:16px;border-bottom-right-radius:0px;padding:3px 10px;width:fit-content;max-width:400px;margin-left:250px;margin-top:-15px;margin-bottom:10px;'> Hello, how are you? </div> <div style='background-color:rgba(42,42,40,0.7);border-radius:16px;border-bottom-left-radius:0px;padding:3px 10px;width:fit-content;max-width:400px;'> I'm fine, thank you. How are you? </div> </div>

🎯 Goals

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

✨ Key Features

📐 Model Specifications

💡 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

🎨 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

📄 License

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

📞 Contact & Support

• —📧 Email: lamapicontact@gmail.com
• —🤗 HuggingFace: Lamapi

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