Lamapi/next-14b

🧠 Next 14B (l310)

Türkiye’s First Reasoning-Capable AI Model — Logical, Analytical, and Enterprise-Ready

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📖 Overview

Next 14B is a 14-billion parameter large language model (LLM) built upon Qwen 3 architecture, trained to achieve superior reasoning and analytical capabilities.
It is Türkiye’s first reasoning-capable AI model, designed to think, infer, and make decisions — not just respond.

Unlike vision-based models, Next 14B focuses on pure cognitive performance, mastering complex problem solving, abstract logic, and human-level understanding in both Turkish and English.

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⚡ Highlights

• 🇹🇷 Türkiye’s first reasoning-capable AI model
• 🧠 Advanced logical, analytical, and inferential reasoning
• 🌍 High multilingual understanding (Turkish, English, and beyond)
• 🏢 Enterprise-grade stability and consistency
• 💬 Instruction-tuned for dialogue, problem solving, and analysis

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📊 Benchmark Performance

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
GPT-5	92.5	87.0	98.4	96.0
Claude Opus 4.1 (Thinking)	~92.0	87.8	84.7	95.4

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🚀 Installation & Usage

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "Lamapi/next-14b"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")

messages = [
    {"role": "system", "content": "You are Next-X1, a reasoning-capable AI assistant created by Lamapi. You think deeply, reason logically, and always answer concisely. Proudly made in Turkey."},
    {"role": "user", "content": "Explain why the sky appears blue using logical reasoning."}
]

prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=150)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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🧩 Key Features

Feature	Description
🧠 Advanced Reasoning	Excels in abstract logic, critical thinking, and long-form analysis.
🇹🇷 Cultural & Multilingual Intelligence	Deep Turkish understanding, alongside fluent English and 30+ languages.
⚙️ Optimized for Efficiency	Available in quantized formats (Q8_0, Q4_K_M, FP16).
🧮 Mathematical & Analytical Skill	Performs exceptionally in structured problem solving and scientific reasoning.
🧩 Non-Vision Architecture	Focused purely on cognitive and linguistic understanding.
🏢 Enterprise Reliability	Consistent, interpretable outputs for professional use cases.

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📐 Model Specifications

Specification	Details
Base Model	Qwen 3
Parameters	14 Billion
Architecture	Transformer (Causal LLM)
Modalities	Text-only
Fine-Tuning	Instruction-tuned and reinforced with cognitive reasoning datasets
Optimizations	Quantization-ready, FP16 support
Primary Focus	Reasoning, logic, decision-making, and language understanding

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🎯 Ideal Use Cases

• Analytical Chatbots for business and enterprise logic
• Research Assistance — scientific, legal, or data-heavy reasoning
• Education & Tutoring — explain concepts step-by-step
• Creative Writing — coherent story logic and worldbuilding
• Code & Algorithm Design — reasoning-based code generation
• Decision Support Systems — scenario evaluation and inference

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💡 Performance Highlights

• Superior Reasoning: Outperforms previous-generation 12B models in logic-based benchmarks.
• Robust Mathematical Understanding: Handles symbolic reasoning and complex equations.
• Consistent Long-Context Memory: Capable of tracking context across multi-turn conversations.
• Professional Reliability: Built for critical enterprise and research applications.

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📄 License

Licensed under the MIT License — free for commercial and non-commercial use. Attribution is appreciated.

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📞 Contact & Support

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

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Next 14B — Türkiye’s first reasoning-capable large language model, combining logical depth, analytical intelligence, and enterprise reliability.