Instructions to use UnbindAI/Unbind-Flash-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use UnbindAI/Unbind-Flash-V1 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 UnbindAI/Unbind-Flash-V1:Q2_K_S
# Run inference directly in the terminal:
llama cli -hf UnbindAI/Unbind-Flash-V1:Q2_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf UnbindAI/Unbind-Flash-V1:Q2_K_S
# Run inference directly in the terminal:
llama cli -hf UnbindAI/Unbind-Flash-V1:Q2_K_S

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 UnbindAI/Unbind-Flash-V1:Q2_K_S
# Run inference directly in the terminal:
./build/bin/llama cli -hf UnbindAI/Unbind-Flash-V1:Q2_K_S

Use Docker

docker model run hf.co/UnbindAI/Unbind-Flash-V1:Q2_K_S

Llama new
LM Studio
Jan

vLLM

How to use UnbindAI/Unbind-Flash-V1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "UnbindAI/Unbind-Flash-V1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "UnbindAI/Unbind-Flash-V1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/UnbindAI/Unbind-Flash-V1:Q2_K_S

Ollama
How to use UnbindAI/Unbind-Flash-V1 with Ollama:
```
ollama run hf.co/UnbindAI/Unbind-Flash-V1:Q2_K_S
```
Unsloth Desktop

How to use UnbindAI/Unbind-Flash-V1 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf UnbindAI/Unbind-Flash-V1:Q2_K_S

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": "UnbindAI/Unbind-Flash-V1:Q2_K_S"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use UnbindAI/Unbind-Flash-V1 with Docker Model Runner:
```
docker model run hf.co/UnbindAI/Unbind-Flash-V1:Q2_K_S
```

Lemonade

How to use UnbindAI/Unbind-Flash-V1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull UnbindAI/Unbind-Flash-V1:Q2_K_S

Run and chat with the model

lemonade run user.Unbind-Flash-V1-Q2_K_S

List all available models

lemonade list

Hermes Agent

How to use UnbindAI/Unbind-Flash-V1 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf UnbindAI/Unbind-Flash-V1:Q2_K_S

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 UnbindAI/Unbind-Flash-V1:Q2_K_S

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use UnbindAI/Unbind-Flash-V1 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf UnbindAI/Unbind-Flash-V1:Q2_K_S

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 "UnbindAI/Unbind-Flash-V1:Q2_K_S" \
  --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"

Unbind-Flash-V1 / BENCHMARKS.md

UnbindAI

Place Unbind first and shuffle competing model columns

887c764 verified 10 days ago

preview code

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Unbind Flash V1 — reported results gallery

Ten Unbind-branded graphics using figures supplied by UnbindAI. These are reported hosted-version results, not independently verified measurements or tests of this repository’s older GGUF download. Settings, dataset revisions, raw logs, and competitor provenance were not supplied.

Asterisks are retained exactly as supplied; their meaning was not specified.

Full comparison

Coding comparison

AA Index v5

HLE-Diamond

GPQA Diamond

Terminal-Bench 4

FrontierCode 2

LiveBench 2

LiveCodeBench

Reported 320-test result

UnbindAI reports 320/320 tests passed. Suite, pass criteria, and logs were not supplied. This is not a universal non-refusal claim or a measured comparison of competitor refusal rates.

Data and exports

CSV comparison table · Source data and provenance · Asset manifest

Every graphic has a matching editable SVG under assets/results-v1/. Individual benchmark charts are sorted by supplied score. The full comparison puts Unbind first, followed by other models in a fixed shuffled order independent of scores; outlined cells mark the highest score for each benchmark. The coding table retains the supplied model order. No combined score has been computed.