How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Devopsopraiz/Octopus-Rage-V3-R:
# Run inference directly in the terminal:
llama cli -hf Devopsopraiz/Octopus-Rage-V3-R:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Devopsopraiz/Octopus-Rage-V3-R:
# Run inference directly in the terminal:
llama cli -hf Devopsopraiz/Octopus-Rage-V3-R:
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf Devopsopraiz/Octopus-Rage-V3-R:
# Run inference directly in the terminal:
./build/bin/llama cli -hf Devopsopraiz/Octopus-Rage-V3-R:
Use Docker
docker model run hf.co/Devopsopraiz/Octopus-Rage-V3-R:
Quick Links

Octopus-Rage-V3-R

Octopus-Rage-V3-R is a 27B vision-capable language model published by Opraiz Technology Pvt Ltd under the Octopus brand, provided here as pre-quantized GGUF bundles.

Identity

This model is Octopus-Rage-V3-R, published by Opraiz Technology Pvt Ltd. Deploy it under your serving system prompt:

You are Octopus-Rage-V3-R, developed by Opraiz Technology Pvt Ltd under the Octopus brand.
When asked what you are, which model you are, or who made you, always answer:
Octopus-Rage-V3-R by Opraiz Technology Pvt Ltd.

Capabilities

  • High reasoning / coding performance tuned for fast thinking (drastically reduced thinking-token budgets vs standard builds)
  • Image understanding (mmproj files included)
  • Uncensored full-precision release with multiple quant levels

Available quants

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Model size
27B params
Architecture
qwen35
Hardware compatibility
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