Image-Text-to-Text
GGUF
llama.cpp
rocm
amd
rocmfp4
rocmfpx
strix-halo
amd-strix-halo
gfx1151
ryzen-ai-max
ryzen-ai-max-395
radeon-8060s
Mixture of Experts
reasoning
multimodal
vision
nex
qwen3.5
quantized
conversational
Instructions to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF 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 kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_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 kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_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 kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
Use Docker
docker model run hf.co/kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
- LM Studio
- Jan
- vLLM
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF", "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/kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
- Ollama
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with Ollama:
ollama run hf.co/kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
- Unsloth Desktop
- Pi
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_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": "kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with Docker Model Runner:
docker model run hf.co/kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
- Lemonade
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
Run and chat with the model
lemonade run user.Nex-N2.5-mini-ROCmFP4-GGUF-Q4_0
List all available models
lemonade list
- Hermes Agent
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_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 kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_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 "kingjones777/Nex-N2.5-mini-ROCmFP4-GGUF:Q4_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"
| PASS think=True multi-arg: args={'city': 'Paris', 'unit': 'celsius'} | |
| FAIL think=True nested-object: exception KeyError('tool_calls') | |
| PASS think=True enum: unit=fahrenheit | |
| PASS think=True correct-decline: content='391' | |
| PASS think=True multi-turn: final='Tokyo is **21°C** and **clear** right now.' | |
| PASS think=True streaming: stream args={'city': 'Rome', 'unit': 'celsius'} | |
| PASS think=True parallel: calls=['lima', 'oslo'] | |
| PASS think=False multi-arg: args={'city': 'Paris', 'unit': 'celsius'} | |
| PASS think=False nested-object: args={'title': 'Design review', 'when': {'date': '2026-10-02', 'time': '14:00'}, 'attendees': ['ana@x.io', 'bo@x.io']} | |
| PASS think=False enum: unit=fahrenheit | |
| PASS think=False correct-decline: content='391' | |
| PASS think=False multi-turn: final='Tokyo is **21°C** and **clear**.' | |
| PASS think=False streaming: stream args={'city': 'Rome', 'unit': 'celsius'} | |
| PASS think=False parallel: calls=['lima', 'oslo'] | |
| {"label": "n-tools-q106-roff", "passed": 13, "total": 14, "detail": {"multi-arg|think=True": true, "nested-object|think=True": false, "enum|think=True": true, "correct-decline|think=True": true, "multi-turn|think=True": true, "streaming|think=True": true, "parallel|think=True": true, "multi-arg|think=False": true, "nested-object|think=False": true, "enum|think=False": true, "correct-decline|think=False": true, "multi-turn|think=False": true, "streaming|think=False": true, "parallel|think=False": true}} | |
| PASS think=True multi-arg: args={'city': 'Paris', 'unit': 'celsius'} | |
| PASS think=True nested-object: args={'title': 'Design review', 'when': {'date': '2026-10-02', 'time': '14:00'}, 'attendees': ['ana@x.io', 'bo@x.io']} | |
| PASS think=True enum: unit=fahrenheit | |
| PASS think=True correct-decline: content='391' | |
| PASS think=True multi-turn: final='Tokyo is **21°C** and **clear**.' | |
| PASS think=True streaming: stream args={'city': 'Rome', 'unit': 'celsius'} | |
| FAIL think=True parallel: calls=['oslo'] | |
| PASS think=False multi-arg: args={'city': 'Paris', 'unit': 'celsius'} | |
| PASS think=False nested-object: args={'title': 'Design review', 'when': {'date': '2026-10-02', 'time': '14:00'}, 'attendees': ['ana@x.io', 'bo@x.io']} | |
| PASS think=False enum: unit=fahrenheit | |
| PASS think=False correct-decline: content='391' | |
| PASS think=False multi-turn: final='Tokyo’s current weather is **21°C and clear**.' | |
| PASS think=False streaming: stream args={'city': 'Rome', 'unit': 'celsius'} | |
| PASS think=False parallel: calls=['lima', 'oslo'] | |
| {"label": "n-tools-q106-roff-r2", "passed": 13, "total": 14, "detail": {"multi-arg|think=True": true, "nested-object|think=True": true, "enum|think=True": true, "correct-decline|think=True": true, "multi-turn|think=True": true, "streaming|think=True": true, "parallel|think=True": false, "multi-arg|think=False": true, "nested-object|think=False": true, "enum|think=False": true, "correct-decline|think=False": true, "multi-turn|think=False": true, "streaming|think=False": true, "parallel|think=False": true}} | |
| PASS think=True multi-arg: args={'city': 'Paris', 'unit': 'celsius'} | |
| PASS think=True nested-object: args={'title': 'Design review', 'when': {'date': '2026-10-02', 'time': '14:00'}, 'attendees': ['ana@x.io', 'bo@x.io']} | |
| PASS think=True enum: unit=fahrenheit | |
| PASS think=True correct-decline: content='391' | |
| PASS think=True multi-turn: final='Tokyo is currently **21°C** with **clear skies**.' | |
| PASS think=True streaming: stream args={'city': 'Rome', 'unit': 'celsius'} | |
| PASS think=True parallel: calls=['lima', 'oslo'] | |
| PASS think=False multi-arg: args={'city': 'Paris', 'unit': 'celsius'} | |
| PASS think=False nested-object: args={'title': 'Design review', 'when': {'date': '2026-10-02', 'time': '14:00'}, 'attendees': ['ana@x.io', 'bo@x.io']} | |
| PASS think=False enum: unit=fahrenheit | |
| PASS think=False correct-decline: content='391' | |
| PASS think=False multi-turn: final='Tokyo’s weather is **21°C and clear**.' | |
| PASS think=False streaming: stream args={'city': 'Rome', 'unit': 'celsius'} | |
| PASS think=False parallel: calls=['lima', 'oslo'] | |
| {"label": "n-tools-q106-roff-r3", "passed": 14, "total": 14, "detail": {"multi-arg|think=True": true, "nested-object|think=True": true, "enum|think=True": true, "correct-decline|think=True": true, "multi-turn|think=True": true, "streaming|think=True": true, "parallel|think=True": true, "multi-arg|think=False": true, "nested-object|think=False": true, "enum|think=False": true, "correct-decline|think=False": true, "multi-turn|think=False": true, "streaming|think=False": true, "parallel|think=False": true}} | |
| {"label": "n-vision-q106-roff-faon", "fa": "on", "mtp": false, "expected": "red,blue,circle,square", "answer": "The image shows two shapes: a red circle on the left and a blue square on the right.", "hits": ["red", "blue", "circle", "square"], "error": null, "server_died": false, "server_log_errors": [], "result": "PASS"} | |
| probe no-kwargs correct-decline {"content": "391", "reasoning_len": 0, "tool_calls": [], "leaks": []} | |
| probe no-kwargs single-word {"content": "ready", "reasoning_len": 0, "tool_calls": [], "leaks": []} | |
| probe no-kwargs multi-arg {"content": "", "reasoning_len": 0, "tool_calls": ["get_weather"], "leaks": []} | |
| probe enable_thinking=false correct-decline {"content": "391", "reasoning_len": 0, "tool_calls": [], "leaks": []} | |
| probe enable_thinking=false single-word {"content": "ready", "reasoning_len": 0, "tool_calls": [], "leaks": []} | |
| probe enable_thinking=false multi-arg {"content": "", "reasoning_len": 0, "tool_calls": ["get_weather"], "leaks": []} | |
| probe reasoning_effort=high correct-decline {"content": "We need answer directly. 391.\n</think>\n\n391", "reasoning_len": 0, "tool_calls": [], "leaks": ["</think>"]} | |
| probe reasoning_effort=high single-word {"content": "We need need output exactly ready.\n</think>\n\nready", "reasoning_len": 0, "tool_calls": [], "leaks": ["</think>"]} | |
| probe reasoning_effort=high multi-arg {"content": "We need need tool. Current weather Paris celsius.\n</think>\n\n", "reasoning_len": 0, "tool_calls": ["get_weather"], "leaks": ["</think>"]} | |
| probe reasoning_effort=medium correct-decline {"content": "\n\n</think>\n\n391", "reasoning_len": 0, "tool_calls": [], "leaks": ["</think>"]} | |
| probe reasoning_effort=medium single-word {"content": "\n\n</think>\n\nready", "reasoning_len": 0, "tool_calls": [], "leaks": ["</think>"]} | |
| probe reasoning_effort=medium multi-arg {"content": "\n\n</think>\n\n", "reasoning_len": 0, "tool_calls": ["get_weather"], "leaks": ["</think>"]} | |
| probe reasoning_effort=none correct-decline {"content": "391", "reasoning_len": 0, "tool_calls": [], "leaks": []} | |
| probe reasoning_effort=none single-word {"content": "ready", "reasoning_len": 0, "tool_calls": [], "leaks": []} | |
| probe reasoning_effort=none multi-arg {"content": "", "reasoning_len": 0, "tool_calls": ["get_weather"], "leaks": []} | |
| NEX_TOOLS_TPL_DONE | |
| rc=0 | |