# 🚀 Next 12B (m200) ### *Türkiye's Advanced Vision-Language Model — High Performance, Multimodal, and Enterprise-Ready* [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![Language: English](https://img.shields.io/badge/Language-Multilingual-red.svg)]() [![HuggingFace](https://img.shields.io/badge/🤗-Lamapi/Next--12B-orange.svg)](https://huggingface.co/Lamapi/next-12b) --- ## 📖 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.

Model	MMLU (5-shot) %	MMLU-Pro %	GSM8K %	MATH %
Next 14B (Thinking)	94.6	93.2	98.8	92.7
Next 12B	92.7	84.4	95.3	87.2
Next 8B (Thinking)	91.0	88.5	96.2	88.0
GPT-5	92.5	87.0	98.4	96.0
Claude Opus 4.1 (Thinking)	~92.0	87.8	84.7	95.4

--- ## 🚀 Installation & Usage ### Use with vision: ```python 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)) ```

Who is in this image?

The image shows Mustafa Kemal Atatürk, the founder and first President of the Republic of Turkey.

### Use without vision: ```python 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)) ```

Hello, how are you?

I'm fine, thank you. How are you?

--- ## 🎯 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. --- ## ✨ Key Features | Feature | Description | | --------------------------------- | ----------------------------------------------------------------------- | | 🔋 Optimized Architecture | Balanced performance and efficiency; supports multiple quantization formats. | | 🖼️ Advanced Vision-Language | Deep understanding of images with sophisticated visual reasoning capabilities. | | 🇹🇷 Professional Turkish Support | Industry-leading Turkish language performance with extensive multilingual reach. | | 🧠 Superior Reasoning | State-of-the-art logical and analytical reasoning for complex tasks. | | 📊 Production-Ready | Reliable, consistent outputs suitable for enterprise applications. | | 🌍 Open Source | Transparent, community-driven, and commercially friendly. | --- ## 📐 Model Specifications | Specification | Details | | ------------------ | ---------------------------------------------------------------------------------- | | Base Model | Gemma 3 | | Parameter Count | 12 Billion | | Architecture | Transformer, causal LLM + Enhanced Vision Encoder | | Fine-Tuning Method | Advanced instruction & multimodal fine-tuning (SFT) on curated Turkish and multilingual datasets | | Optimizations | Q8_0, Q4_K_M, F16, F32 quantizations for flexible deployment options | | Modalities | Text & Image | | Use Cases | Advanced image captioning, multimodal QA, text generation, complex reasoning, creative storytelling, enterprise applications | --- ## 💡 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](mailto:lamapicontact@gmail.com) * 🤗 **HuggingFace:** [Lamapi](https://huggingface.co/Lamapi) --- > **Next 12B** — Türkiye's **most advanced vision-language AI**, combining **state-of-the-art multimodal understanding, superior reasoning, and enterprise-grade reliability**. [![Follow on HuggingFace](https://img.shields.io/badge/Follow-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/Lamapi)