Instructions to use ubergarm/Kimi-K2.6-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ubergarm/Kimi-K2.6-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ubergarm/Kimi-K2.6-GGUF", filename="IQ3_K/Kimi-K2.6-IQ3_K-00001-of-00012.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ubergarm/Kimi-K2.6-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ubergarm/Kimi-K2.6-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf ubergarm/Kimi-K2.6-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ubergarm/Kimi-K2.6-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf ubergarm/Kimi-K2.6-GGUF:Q2_K
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 ubergarm/Kimi-K2.6-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf ubergarm/Kimi-K2.6-GGUF:Q2_K
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 ubergarm/Kimi-K2.6-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf ubergarm/Kimi-K2.6-GGUF:Q2_K
Use Docker
docker model run hf.co/ubergarm/Kimi-K2.6-GGUF:Q2_K
- LM Studio
- Jan
- vLLM
How to use ubergarm/Kimi-K2.6-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ubergarm/Kimi-K2.6-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": "ubergarm/Kimi-K2.6-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ubergarm/Kimi-K2.6-GGUF:Q2_K
- Ollama
How to use ubergarm/Kimi-K2.6-GGUF with Ollama:
ollama run hf.co/ubergarm/Kimi-K2.6-GGUF:Q2_K
- Unsloth Studio
How to use ubergarm/Kimi-K2.6-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ubergarm/Kimi-K2.6-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ubergarm/Kimi-K2.6-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ubergarm/Kimi-K2.6-GGUF to start chatting
- Pi
How to use ubergarm/Kimi-K2.6-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf ubergarm/Kimi-K2.6-GGUF:Q2_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "ubergarm/Kimi-K2.6-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use ubergarm/Kimi-K2.6-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf ubergarm/Kimi-K2.6-GGUF:Q2_K
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 ubergarm/Kimi-K2.6-GGUF:Q2_K
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use ubergarm/Kimi-K2.6-GGUF with Docker Model Runner:
docker model run hf.co/ubergarm/Kimi-K2.6-GGUF:Q2_K
- Lemonade
How to use ubergarm/Kimi-K2.6-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ubergarm/Kimi-K2.6-GGUF:Q2_K
Run and chat with the model
lemonade run user.Kimi-K2.6-GGUF-Q2_K
List all available models
lemonade list
| {# vibe patched to work more like Qwen3.6 e.g. enable_thinking and similar preserve_thinking behavior #} | |
| {%- macro render_content(msg) -%} | |
| {%- set c = msg.get('content') -%} | |
| {%- if c is string -%} | |
| {{ c }} | |
| {%- elif c is not none -%} | |
| {% for content in c -%} | |
| {% if content['type'] == 'image' or content['type'] == 'image_url' -%} | |
| <|media_begin|>image<|media_content|><|media_pad|><|media_end|> | |
| {% elif content['type'] == 'video' or content['type']== 'video_url'-%} | |
| <|kimi_k25_video_placeholder|> | |
| {% else -%} | |
| {{ content['text'] }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {% macro set_roles(message) -%} | |
| {%- set role_name = message.get('name') or message['role'] -%} | |
| {%- if message['role'] == 'user' -%} | |
| <|im_user|>{{role_name}}<|im_middle|> | |
| {%- elif message['role'] == 'assistant' -%} | |
| <|im_assistant|>{{role_name}}<|im_middle|> | |
| {%- else -%} | |
| <|im_system|>{{role_name}}<|im_middle|> | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- macro render_toolcalls(message) -%} | |
| <|tool_calls_section_begin|> | |
| {%- for tool_call in message['tool_calls'] -%} | |
| {%- set formatted_id = tool_call['id'] -%} | |
| <|tool_call_begin|>{{ formatted_id }}<|tool_call_argument_begin|>{% if tool_call['function']['arguments'] is string %}{{ tool_call['function']['arguments'] }}{% else %}{{ tool_call['function']['arguments'] | tojson }}{% endif %}<|tool_call_end|> | |
| {%- endfor -%} | |
| <|tool_calls_section_end|> | |
| {%- endmacro -%} | |
| {# Find last non-tool-call assistant message. If preserve_thinking, keep -1 so hist is empty and all msgs use suffix (retain reasoning). #} | |
| {%- set ns = namespace(last_non_tool_call_assistant_msg=-1) -%} | |
| {%- if preserve_thinking is not defined or preserve_thinking is not true -%} | |
| {%- for idx in range(messages|length-1, -1, -1) -%} | |
| {%- if messages[idx]['role'] == 'assistant' and not messages[idx].get('tool_calls') -%} | |
| {%- set ns.last_non_tool_call_assistant_msg = idx -%} | |
| {%- break -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {# split all messages into history & suffix, reasoning_content in suffix should be reserved.#} | |
| {%- set hist_msgs = messages[:ns.last_non_tool_call_assistant_msg+1] -%} | |
| {%- set suffix_msgs = messages[ns.last_non_tool_call_assistant_msg+1:] -%} | |
| {%- if tools -%} | |
| {%- if tools_ts_str -%} | |
| <|im_system|>tool_declare<|im_middle|>{{ tools_ts_str }}<|im_end|> | |
| {%- else -%} | |
| <|im_system|>tool_declare<|im_middle|>{{ tools | tojson(separators=(',', ':')) }}<|im_end|> | |
| {%- endif -%} | |
| {%- endif -%} | |
| {%- for message in hist_msgs -%} | |
| {{set_roles(message)}} | |
| {%- if message['role'] == 'assistant' -%} | |
| <think></think>{{render_content(message)}} | |
| {%- if message.get('tool_calls') -%} | |
| {{render_toolcalls(message)}} | |
| {%- endif -%} | |
| {%- elif message['role'] == 'tool' -%} | |
| {%- set tool_call_id = message.tool_call_id -%} | |
| ## Return of {{ tool_call_id }} | |
| {{render_content(message)}} | |
| {%- elif message['content'] is not none -%} | |
| {{render_content(message)}} | |
| {%- endif -%} | |
| <|im_end|> | |
| {%- endfor -%} | |
| {%- for message in suffix_msgs -%} | |
| {{set_roles(message)}} | |
| {%- if message['role'] == 'assistant' -%} | |
| {%- if enable_thinking is defined and enable_thinking is false and (preserve_thinking is not defined or preserve_thinking is not true) -%} | |
| <think></think>{{render_content(message)}} | |
| {%- else -%} | |
| {%- set rc = message.get('reasoning', message.get('reasoning_content', '')) -%} | |
| <think>{{rc}}</think>{{render_content(message)}} | |
| {%- endif -%} | |
| {%- if message.get('tool_calls') -%} | |
| {{render_toolcalls(message)}} | |
| {%- endif -%} | |
| {%- elif message['role'] == 'tool' -%} | |
| {%- set tool_call_id = message.tool_call_id -%} | |
| ## Return of {{ tool_call_id }} | |
| {{render_content(message)}} | |
| {%- elif message['content'] is not none -%} | |
| {{render_content(message)}} | |
| {%- endif -%} | |
| <|im_end|> | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| <|im_assistant|>assistant<|im_middle|> | |
| {%- if enable_thinking is defined and enable_thinking is false -%} | |
| <think></think> | |
| {%- else -%} | |
| <think> | |
| {%- endif -%} | |
| {%- endif -%} | |