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 / assets /benchmarks /source-data.json

UnbindAI

Apply Unbind Flash V1 launch branding to benchmark series

dec2bcc verified 10 days ago

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3.06 kB

{
  "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/raw/main/README.md",
  "model_names": [
    "DeepSeek V4.1 Flash 1017",
    "DeepSeek V4.1 Flash",
    "K3",
    "GLM-5.3",
    "GPT-5.6 Sol",
    "Opus 5"
  ],
  "highlight_index": 0,
  "series": [
    {
      "id": "01-deepswe",
      "title": "Software engineering",
      "benchmark": "DeepSWE v1.1",
      "values": [
        77.0,
        74.2,
        67.5,
        66.9,
        73.0,
        74.0
      ],
      "note": "Mini-SWE-V2 harness. Publisher-reported benchmark scores."
    },
    {
      "id": "02-terminal",
      "title": "Terminal tasks",
      "benchmark": "Terminal-Bench 4.0",
      "values": [
        42.3,
        31.2,
        12.6,
        37.9,
        39.9,
        51.8
      ],
      "note": "Claude Code harness. Publisher-reported benchmark scores."
    },
    {
      "id": "03-hle",
      "title": "Reasoning without tools",
      "benchmark": "HLE without tools",
      "values": [
        42.6,
        36.8,
        43.5,
        null,
        44.5,
        56.3
      ],
      "note": "Full HLE figures only. GLM-5.3 omitted: the source gives a text-only subset score."
    },
    {
      "id": "04-program",
      "title": "Programming tasks",
      "benchmark": "ProgramBench",
      "values": [
        29.1,
        20.3,
        17.5,
        19.0,
        23.0,
        37.0
      ],
      "note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
    },
    {
      "id": "05-nl2repo",
      "title": "From instructions to repositories",
      "benchmark": "NL2Repo-Bench",
      "values": [
        68.2,
        65.4,
        58.0,
        58.0,
        56.8,
        75.3
      ],
      "note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
    },
    {
      "id": "06-automation",
      "title": "Automation tasks",
      "benchmark": "Automation-Bench v1.0.6",
      "values": [
        60.5,
        54.8,
        46.7,
        48.8,
        45.8,
        50.3
      ],
      "note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
    },
    {
      "id": "07-agents",
      "title": "Agent evaluation",
      "benchmark": "Agents’ Last Exam",
      "values": [
        35.4,
        31.8,
        27.6,
        28.5,
        26.7,
        28.6
      ],
      "note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
    },
    {
      "id": "08-apex",
      "title": "Apex benchmark",
      "benchmark": "Apex Bench v1.1",
      "values": [
        72.1,
        64.6,
        47.8,
        56.6,
        54.3,
        65.8
      ],
      "note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
    }
  ],
  "branding_name": "Unbind Flash V1",
  "highlight_display_label": "Unbind Flash V1 · base model"
}

	{
	"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017/raw/main/README.md",
	"model_names": [
	"DeepSeek V4.1 Flash 1017",
	"DeepSeek V4.1 Flash",
	"K3",
	"GLM-5.3",
	"GPT-5.6 Sol",
	"Opus 5"
	],
	"highlight_index": 0,
	"series": [
	{
	"id": "01-deepswe",
	"title": "Software engineering",
	"benchmark": "DeepSWE v1.1",
	"values": [
	77.0,
	74.2,
	67.5,
	66.9,
	73.0,
	74.0
	],
	"note": "Mini-SWE-V2 harness. Publisher-reported benchmark scores."
	},
	{
	"id": "02-terminal",
	"title": "Terminal tasks",
	"benchmark": "Terminal-Bench 4.0",
	"values": [
	42.3,
	31.2,
	12.6,
	37.9,
	39.9,
	51.8
	],
	"note": "Claude Code harness. Publisher-reported benchmark scores."
	},
	{
	"id": "03-hle",
	"title": "Reasoning without tools",
	"benchmark": "HLE without tools",
	"values": [
	42.6,
	36.8,
	43.5,
	null,
	44.5,
	56.3
	],
	"note": "Full HLE figures only. GLM-5.3 omitted: the source gives a text-only subset score."
	},
	{
	"id": "04-program",
	"title": "Programming tasks",
	"benchmark": "ProgramBench",
	"values": [
	29.1,
	20.3,
	17.5,
	19.0,
	23.0,
	37.0
	],
	"note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
	},
	{
	"id": "05-nl2repo",
	"title": "From instructions to repositories",
	"benchmark": "NL2Repo-Bench",
	"values": [
	68.2,
	65.4,
	58.0,
	58.0,
	56.8,
	75.3
	],
	"note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
	},
	{
	"id": "06-automation",
	"title": "Automation tasks",
	"benchmark": "Automation-Bench v1.0.6",
	"values": [
	60.5,
	54.8,
	46.7,
	48.8,
	45.8,
	50.3
	],
	"note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
	},
	{
	"id": "07-agents",
	"title": "Agent evaluation",
	"benchmark": "Agents’ Last Exam",
	"values": [
	35.4,
	31.8,
	27.6,
	28.5,
	26.7,
	28.6
	],
	"note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
	},
	{
	"id": "08-apex",
	"title": "Apex benchmark",
	"benchmark": "Apex Bench v1.1",
	"values": [
	72.1,
	64.6,
	47.8,
	56.6,
	54.3,
	65.8
	],
	"note": "Publisher-reported benchmark scores. Additional per-row settings are not specified."
	}
	],
	"branding_name": "Unbind Flash V1",
	"highlight_display_label": "Unbind Flash V1 · base model"
	}