NandoG-AI/Nex-N2.5-mini-GGUF

🧠 Nex-N2.5-mini — GGUF

GGUF quantizations of **nex-agi/Nex-N2.5-mini** for use with `llama.cpp` and compatible runtimes (LM Studio, Open WebUI, KoboldCpp, etc.).

Multimodal (vision) support is included via a separate mmproj projector file — see the Multimodal Support section.

📖 About Nex-N2.5

Nex-N2.5 is a next-generation family of agentic models designed for long-horizon reasoning and real-world task execution.

Building on the multimodal foundations of Nex-N2, the Nex-N2.5 family introduces significant improvements in:

• —Software engineering
• —Tool calling
• —Browser use
• —Computer use
• —Agentic workflows
• —Reasoning
• —Multimodal understanding
• —Long-context processing

Unlike traditional chat models, Nex-N2.5 is designed to continuously interact with environments, verify outcomes, self-correct, and execute complex multi-step workflows.

The family consists of:

• —Nex-N2.5-mini (this repository)
• —Nex-N2.5-Pro
• —Nex-N2.5-Max

The original model supports a native context length of 262,144 tokens (256K).

📊 Model Information

Primary use cases: coding, software development, autonomous agents, web automation, computer use, research, knowledge work, and multimodal tasks.

📥 Available Quantizations

⭐ Recommended

⚡ Performance / Low Memory

🎯 Maximum Quality

📂 Files

Download a single quant

hf download <your-username>/Nex-N2.5-mini-GGUF \
  Nex-N2.5-mini-Q4_K_M.gguf \
  --local-dir ./Nex-N2.5-mini-GGUF

For vision, also download mmproj-Nex-N2.5-mini-F16.gguf.

🖼️ Multimodal Support

This repository includes a vision projector for image-enabled inference:

mmproj-Nex-N2.5-mini-F16.gguf

Pass it alongside your chosen quant with --mmproj:

llama-server \
  -m Nex-N2.5-mini-Q4_K_M.gguf \
  --mmproj mmproj-Nex-N2.5-mini-F16.gguf \
  --jinja \
  -c 8192

Text-only usage does not require the projector.

⚙️ Recommended Sampling Parameters

Original Nex-AGI recommendation:

temperature = 0.7
top_p       = 0.95
top_k       = 40

For deterministic benchmarking (identical input → identical output):

temperature = 0.0
top_p       = 1.0
top_k       = 0

💭 Thinking Modes

Nex-N2.5 supports multiple reasoning modes, usually exposed through your frontend's reasoning settings:

🖥️ llama.cpp Usage

Chat (CLI)

llama-cli \
  -m Nex-N2.5-mini-Q4_K_M.gguf \
  -c 8192 \
  --jinja

OpenAI-compatible server

llama-server \
  -m Nex-N2.5-mini-Q4_K_M.gguf \
  --jinja \
  -c 8192 \
  --host 0.0.0.0 \
  --port 8080

Increase -c (context size) as memory allows — the model supports up to:

262144 tokens

✅ Features

• —262K context support
• —Tool calling
• —Reasoning / thinking modes
• —Multimodal vision support
• —Agentic workflows
• —Coding-optimized
• —OpenAI-compatible serving
• —Compatible with llama.cpp, LM Studio, Open WebUI, and KoboldCpp

🔗 Links

• —Original model: nex-agi/Nex-N2.5-mini
• —Nex-AGI: nex-agi.com
• —OpenRouter: openrouter.ai/nex-agi/nex-n2.5-mini

🙏 Credits

• —Original model: Nex-AGI
• —GGUF conversion & quantization: Nando Gaarenstroom
• —Inference runtime: ggml-org/llama.cpp

Special thanks to the local AI community for testing and feedback.

⭐ Support

If these GGUF quantizations are useful to you, please consider:

• —❤️ Liking the repository
• —📊 Sharing benchmark results
• —🐛 Reporting issues
• —🧪 Contributing testing feedback

Happy local inferencing 🚀