Instructions to use lmstudio-community/Qwen3.5-35B-A3B-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 lmstudio-community/Qwen3.5-35B-A3B-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 lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
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 lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
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 lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use lmstudio-community/Qwen3.5-35B-A3B-GGUF with Ollama:
ollama run hf.co/lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use lmstudio-community/Qwen3.5-35B-A3B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
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": "lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use lmstudio-community/Qwen3.5-35B-A3B-GGUF with Docker Model Runner:
docker model run hf.co/lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
- Lemonade
How to use lmstudio-community/Qwen3.5-35B-A3B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3.5-35B-A3B-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use lmstudio-community/Qwen3.5-35B-A3B-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 lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
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 lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use lmstudio-community/Qwen3.5-35B-A3B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M
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 "lmstudio-community/Qwen3.5-35B-A3B-GGUF:Q4_K_M" \ --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"
lmstudio temp fix for tool calling
UPDATE: LM Studio 0.4.5 (Build 1) fixed the issue, and stock prompt template works fine now!
I was getting "Failed to parse tool call" for js-sandbox and "Error rendering prompt with jinja template" for multiple files in chat (single file worked) and when in opencode some tool calling didn't work either. So I pasted the prompt template to fix these two issues and now tool calling works in both lmstudio and opencode.
Hope this helps someone, but the generated template fix looks pretty bruteforced, maybe theres a better way?
Here's the template:
{%- set image_count = namespace(value=0) %}
{%- set video_count = namespace(value=0) %}
{%- macro render_content(content, do_vision_count) %}
{%- if content is string %}
{{- content }}
{%- elif content is iterable and content is not mapping %}
{%- for item in content %}
{%- if item.type == 'image' or 'image' in item %}
{%- if do_vision_count %} {%- set image_count.value = image_count.value + 1 %} {%- endif %}
{{- ('Picture ' ~ image_count.value ~ ': ' if add_vision_id else '') ~ '<|vision_start|><|image_pad|><|vision_end|>' }}
{%- elif item.type == 'video' or 'video' in item %}
{%- if do_vision_count %} {%- set video_count.value = video_count.value + 1 %} {%- endif %}
{{- ('Video ' ~ video_count.value ~ ': ' if add_vision_id else '') ~ '<|vision_start|><|video_pad|><|vision_end|>' }}
{%- elif 'text' in item %}
{{- item.text }}
{%- endif %}
{%- endfor %}
{%- endif %}
{%- endmacro %}
{%- if tools %}
{{- '<|im_start|>system\n# Tools\n\nYou have access to the following functions:\n\n<tools>\n' }}
{%- for tool in tools %}
{{- tool | tojson ~ '\n' }}
{%- endfor %}
{{- '</tools>\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n{"name": "function_name", "arguments": {"param_1": "value"}}\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: a valid JSON object must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
{%- if messages and messages[0].role == 'system' %}
{{- '\n\n' ~ render_content(messages[0].content, false)|trim }}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- elif messages and messages[0].role == 'system' %}
{{- '<|im_start|>system\n' ~ render_content(messages[0].content, false)|trim ~ '<|im_end|>\n' }}
{%- endif %}
{%- set ns = namespace(searching=true, last_query_index=messages|length - 1) %}
{%- for message in messages[::-1] %}
{%- if ns.searching and message.role == "user" %}
{%- set content = render_content(message.content, false)|trim %}
{%- if not (content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
{%- set ns.searching = false %}
{%- set ns.last_query_index = (messages|length - 1) - loop.index0 %}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- for message in messages %}
{%- set content = render_content(message.content, true)|trim %}
{%- if message.role == "system" and not loop.first %}
{{- '<|im_start|>system\n' ~ content ~ '<|im_end|>\n' }}
{%- elif message.role == "user" %}
{{- '<|im_start|>user\n' ~ content ~ '<|im_end|>\n' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>assistant\n' }}
{%- set reasoning = message.reasoning_content | default('', true) %}
{%- if not reasoning and '</think>' in content %}
{%- set reasoning = content.split('</think>')[0].split('<think>')[-1]|trim %}
{%- set content = content.split('</think>')[-1]|trim %}
{%- endif %}
{%- if loop.index0 > ns.last_query_index and reasoning %}
{{- '<think>\n' ~ reasoning ~ '\n</think>\n\n' }}
{%- endif %}
{{- content }}
{%- if message.tool_calls %}
{%- for tool_call in message.tool_calls %}
{%- set tc = tool_call.function | default(tool_call) %}
{%- set args = tc.arguments | default('{}') %}
{%- set args_str = args if args is string else args | tojson %}
{{- '\n<tool_call>\n{"name": "' ~ tc.name ~ '", "arguments": ' ~ args_str ~ '}\n</tool_call>' }}
{%- endfor %}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if loop.previtem and loop.previtem.role != "tool" %} {{- '<|im_start|>user' }} {%- endif %}
{{- '\n<tool_response>\n' ~ content ~ '\n</tool_response>' }}
{%- if loop.last or (loop.nextitem and loop.nextitem.role != "tool") %} {{- '<|im_end|>\n' }} {%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' ~ ('<think>\n' if enable_thinking|default(true) else '<think>\n\n</think>\n\n') }}
{%- endif %}
LM Studio build 0.4.5+2 has just fixed it, I reverted back to the default Prompt Template from the one posted above and it works fine.
LM Studio build 0.4.5+2 has just fixed it, I reverted back to the default Prompt Template from the one posted above and it works fine.
The OpenClaw call still throws an error, but the one provided by the original poster works fine.