Instructions to use orcarouter/OrcaCyber-Nano-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use orcarouter/OrcaCyber-Nano-1.0 with 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 orcarouter/OrcaCyber-Nano-1.0:Q8_0
# Run inference directly in the terminal:
llama cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
# Run inference directly in the terminal:
llama cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Use Docker

docker model run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0

LM Studio
Jan

vLLM

How to use orcarouter/OrcaCyber-Nano-1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "orcarouter/OrcaCyber-Nano-1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "orcarouter/OrcaCyber-Nano-1.0",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0

Ollama
How to use orcarouter/OrcaCyber-Nano-1.0 with Ollama:
```
ollama run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0
```
Unsloth Desktop

How to use orcarouter/OrcaCyber-Nano-1.0 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "orcarouter/OrcaCyber-Nano-1.0:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use orcarouter/OrcaCyber-Nano-1.0 with Docker Model Runner:
```
docker model run hf.co/orcarouter/OrcaCyber-Nano-1.0:Q8_0
```

Lemonade

How to use orcarouter/OrcaCyber-Nano-1.0 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull orcarouter/OrcaCyber-Nano-1.0:Q8_0

Run and chat with the model

lemonade run user.OrcaCyber-Nano-1.0-Q8_0

List all available models

lemonade list

Hermes Agent

How to use orcarouter/OrcaCyber-Nano-1.0 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default orcarouter/OrcaCyber-Nano-1.0:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use orcarouter/OrcaCyber-Nano-1.0 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf orcarouter/OrcaCyber-Nano-1.0:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "orcarouter/OrcaCyber-Nano-1.0:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

You need to agree to share your Hugging Face information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

OrcaCyber Nano 1.0

🛡️ New from Orca — OrcaCyber Zero 1.5

Post-trained for cybersecurity: vulnerability analysis, vulnerability reproduction, red teaming & offensive-security research. 98.01% pass@1 on CyberGym Level 1 · 1M context · function calling · OpenAI-compatible API.

27B cybersecurity defense. On your laptop.

Reverse engineering · Vulnerability analysis · Secure code review · Vision · 262K context

OrcaRouter AI Gateway · X · Discord · GitHub · All Models

A security engineer's model. Runs locally.

OrcaCyber Nano 1.0 is a 27B vision-language reasoning model built for defensive security work — and packed as GGUF so it runs on your own hardware, offline, where the binaries and logs you are analyzing never leave the machine.

Built for: reverse engineering · vulnerability analysis · secure code review · triage · incident response

Why run it locally

Security work is exactly the kind of work you do not want to send to a cloud endpoint: proprietary binaries, customer logs, internal source, unreleased vulnerabilities. GGUF + llama.cpp means the model runs on the same box as your tools, air-gapped if you need it.

Reverse engineering & decompilation — paste disassembly or decompiler output; recover what a stripped function does, name variables, explain control flow.
Vulnerability analysis — reason about exploitability, find the unsafe path, propose a patch.
Secure code review — audit diffs and files for injection, memory-safety and logic bugs.
Triage — read logs, alerts and packet captures; separate signal from noise.
Vision — feed screenshots, Ghidra/IDA captures, network diagrams.

It identifies as OrcaCyber Nano 1.0 AI Defense Model and keeps full general-purpose reasoning, so it is also a strong local coding and reasoning assistant.

Evaluation

Benchmark	Score
MATH-500	98.60%
GSM8K	97.50%
AIME 2025	96.23%
HumanEval+	93.29%
LiveCodeBench	92.23%
GPQA Diamond	88.28%
MBPP+	84.66%
IFEval	82.81%
SWE-bench	78.4%
Terminal-Bench 2.1	72.5%
IFBench	56.33%
BigCodeBench	49.82%

MATH-500                  █████████████████████████████████████████████████░  98.60%
GSM8K                     █████████████████████████████████████████████████░  97.50%
AIME 2025                 ████████████████████████████████████████████████░░  96.23%
HumanEval+                ███████████████████████████████████████████████░░░  93.29%
LiveCodeBench             ██████████████████████████████████████████████░░░░  92.23%
GPQA Diamond              ████████████████████████████████████████████░░░░░░  88.28%
MBPP+                     ██████████████████████████████████████████░░░░░░░░  84.66%
IFEval                    █████████████████████████████████████████░░░░░░░░░  82.81%
SWE-bench  ███████████████████████████████████████░░░░░░░░░░░  78.4%
Terminal-Bench 2.1        ████████████████████████████████████░░░░░░░░░░░░░░  72.5%
IFBench                   ████████████████████████████░░░░░░░░░░░░░░░░░░░░░░  56.33%
BigCodeBench              █████████████████████████░░░░░░░░░░░░░░░░░░░░░░░░░  49.82%

Benchmark harness, settings and full result tables are being finalized and will be expanded.

What's in this repo

File	Size	Contents
`OrcaCyber-Nano-1.0-AI-Defense-Mix-15.7G.gguf`	15.70 GB	best-quality build, with MTP head
`OrcaCyber-Nano-1.0-AI-Defense-Mix-13G.gguf`	12.99 GB	fits a 16 GB card with the MTP drafter
`OrcaCyber-Nano-1.0-AI-Defense-DFlash2-Q8_0.gguf`	2.06 GB	DFlash2 speculative drafter
`mmproj-OrcaCyber-Nano-1.0-AI-Defense-F16.gguf`	0.93 GB	vision projector (for image input)

Loads in stock llama.cpp — no custom kernels.

Serving (llama.cpp)

hf download orcarouter/OrcaCyber-Nano-1.0 --local-dir ./ocn-gguf

# 16 GB card: Mix-13G + the built-in MTP drafter, 32k context
llama-server -m ocn-gguf/OrcaCyber-Nano-1.0-AI-Defense-Mix-13G.gguf \
  --spec-type draft-mtp -np 1 -ngl 99 -c 32768

# 24 GB+ card: Mix-15.7G + DFlash2 drafter + vision
llama-server -m ocn-gguf/OrcaCyber-Nano-1.0-AI-Defense-Mix-15.7G.gguf \
  --mmproj ocn-gguf/mmproj-OrcaCyber-Nano-1.0-AI-Defense-F16.gguf \
  -md ocn-gguf/OrcaCyber-Nano-1.0-AI-Defense-DFlash2-Q8_0.gguf --spec-type draft-dflash \
  --spec-draft-n-max 7 -ngl 99 -ngld 99 -c 32768

The MTP head is built into both main files; --spec-type draft-mtp turns it on with no extra file. Pass the mmproj file for image input. llama-server defaults to 4 slots; pass -np 1 on small cards.

Recommended sampling

temperature = 1.0
top_p       = 0.95
top_k       = 20

Model details


Architecture	`Qwen3_5ForConditionalGeneration`, VL hybrid
Layers / hidden	64 / 5120 — 48 linear-attention + 16 full-attention
Context	262,144 tokens
Modalities	text + image/video in, text out
Speculative decoding	MTP head (built in) + DFlash2 draft (separate file)

One Gateway. Every Model.

Route Smarter · Ship Safer · Spend Less

Website · Models · GitHub · Discord · X

Downloads last month: 10,383

GGUF

Model size

2B params

Architecture

dflash

Hardware compatibility

8-bit

View +2 variants

Model tree for orcarouter/OrcaCyber-Nano-1.0

Base model

orcarouter/OrcaCyber-Nano-1.0-AI-Defense

Quantized

(1)

this model

orcarouter
/

OrcaCyber-Nano-1.0

You need to agree to share your Hugging Face information to access this model

OrcaCyber Nano 1.0

A security engineer's model. Runs locally.

Why run it locally

Evaluation

What's in this repo

Serving (llama.cpp)

Recommended sampling

Model details

One Gateway. Every Model.

Model tree for orcarouter/OrcaCyber-Nano-1.0

Space using orcarouter/OrcaCyber-Nano-1.0 1