⚡ Next 2 Fast (4B)
Global Speed, Multimodal Intelligence — Engineered by Lamapi
🌍 Overview
Next 2 Fast is a state-of-the-art 4-billion parameter Multimodal Vision-Language Model (VLM) designed for high-performance reasoning across languages and modalities.
Developed by Lamapi, a leading AI research lab in Türkiye, this model represents a leap in efficiency, bridging the gap between massive commercial models and accessible, open-source intelligence. Built upon the Gemma 3 architecture and refined with our proprietary SFT and DPO techniques, Next 2 Fast is not just a language model—it is a global reasoning engine that sees, understands, and communicates fluently in English, Turkish, German, French, Spanish, and 25+ other languages.
Why Next 2 Fast?
- ⚡ Global Performance: Tuned for complex reasoning in English and multilingual contexts, outperforming larger models.
- 👁️ Vision & Text: Seamlessly processes images and text to generate code, descriptions, and analysis.
- 🚀 Unmatched Speed: Optimized for low-latency inference, making it ~2x faster than previous generations.
- 🔋 Efficient Deployment: Runs smoothly on consumer hardware (8GB VRAM) using 4-bit/8-bit quantization.
🏆 Benchmark Performance
Next 2 Fast delivers flagship-level performance in a compact 4B size, proving that efficiency does not require sacrificing intelligence.
| Model | Params | MMLU (5-shot) % | MMLU-Pro % | GSM8K % | MATH % |
|---|---|---|---|---|---|
| ⚡ Next 2 Fast | 4B | 85.1 | 67.4 | 83.5 | 71.2 |
| Gemma 3 4B | 4B | 82.0 | 64.5 | 80.1 | 68.0 |
| Llama 3.2 3B | 3B | 63.4 | 52.1 | 45.2 | 42.8 |
| Phi-3.5 Mini | 3.8B | 84.0 | 66.0 | 82.0 | 69.5 |
🚀 Quick Start
Next 2 Fast is fully compatible with the Hugging Face transformers library.
🖼️ Multimodal Inference (Vision + Text):
from transformers import AutoTokenizer, AutoModelForCausalLM, AutoProcessor
from PIL import Image
import torch
model_id = "thelamapi/next2-fast"
# Load Model & Processor
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
processor = AutoProcessor.from_pretrained(model_id)
tokenizer = AutoTokenizer.from_pretrained(model_id)
# Load Image
image = Image.open("image.jpg")
# Create Multimodal Prompt
messages = [
{
"role": "system",
"content": [{"type": "text", "text": "You are Next-2, an AI assistant created by Lamapi. Provide concise and accurate analysis."}]
},
{
"role": "user",
"content": [
{"type": "image", "image": image},
{"type": "text", "text": "Analyze this image and explain in English."}
]
}
]
# Process & Generate
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = processor(text=prompt, images=[image], return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(output[0], skip_special_tokens=True))
💬 Text-Only Chat (Global Reasoning):
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "Lamapi/next-2-fast"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
messages = [
{"role": "system", "content": "You are Next 2 Fast, an advanced AI assistant."},
{"role": "user", "content": "Explain the concept of entropy in thermodynamics simply."}
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(output[0], skip_special_tokens=True))
🌐 Key Features
| Feature | Description |
|---|---|
| 🌍 True Multilingualism | Fluent in English, Turkish, German, French, Spanish, and more. No "translation-ese." |
| 🧠 Visual Intelligence | Can read charts, identify objects, and reason about visual scenes effectively. |
| ⚡ High Efficiency | Designed for speed. Ideal for edge devices, local deployment, and real-time apps. |
| 💻 Code & Math | Strong capabilities in Python coding, debugging, and solving mathematical problems. |
| 🛡️ Global Alignment | Fine-tuned with a diverse dataset to ensure safety and neutrality across cultures. |
🎯 Mission
At Lamapi, our mission is to build the Next generation of intelligence that is accessible to everyone, everywhere.
Next 2 Fast proves that world-class AI innovation isn't limited to Silicon Valley. By combining efficient architecture with high-quality global datasets, we provide a powerful tool for researchers, developers, and businesses worldwide.
📄 License
This model is open-sourced under the MIT License. It is free for academic and commercial use.
📞 Contact & Ecosystem
We are Lamapi.
- 📧 Contact: Mail
- 🤗 HuggingFace: Company Page
Next 2 Fast — Global Intelligence. Lightning Speed. Powered by Lamapi.
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