how to set enable_thinking=False in vllm deploy cmd

[DragonFive]

in offline inference,there is a option in apply_chat_template: enable_thinking=False, set it to no_thinking mode

but in online depoly environment, how to set it no_thinking?

vllm serve Qwen/Qwen3-8B --port 8000 --enable-reasoning-parser --reasoning-parser deepseek_r1

[cynial]

https://qwen.readthedocs.io/en/latest/deployment/vllm.html#thinking-non-thinking-modes

curl http://localhost:8000/v1/chat/completions -H "Content-Type: application/json" -d '{
  "model": "Qwen/Qwen3-8B",
  "messages": [
    {"role": "user", "content": "Give me a short introduction to large language models."}
  ],
  "temperature": 0.7,
  "top_p": 0.8,
  "top_k": 20,
  "max_tokens": 8192,
  "presence_penalty": 1.5,
  "chat_template_kwargs": {"enable_thinking": false}
}'

[TatsuhiroC]

I wonder how to set, enable_thinking=False, on ollama and open-webui.

qwen3 works different with cogito

[zhangkaifang]

移除参数 --reasoning-parser（以及 --enable-reasoning），移除这2个参数好像不起作用。

[jklj077]

To completely disable the thinking mode, you could use a custom chat template.

{%- if tools %}
    {{- '<|im_start|>system\n' }}
    {%- if messages[0].role == 'system' %}
        {{- messages[0].content + '\n\n' }}
    {%- endif %}
    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
    {%- for tool in tools %}
        {{- "\n" }}
        {{- tool | tojson }}
    {%- endfor %}
    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
{%- else %}
    {%- if messages[0].role == 'system' %}
        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
    {%- endif %}
{%- endif %}
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
{%- for message in messages[::-1] %}
    {%- set index = (messages|length - 1) - loop.index0 %}
    {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
        {%- set ns.multi_step_tool = false %}
        {%- set ns.last_query_index = index %}
    {%- endif %}
{%- endfor %}
{%- for message in messages %}
    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
    {%- elif message.role == "assistant" %}
        {%- set content = message.content %}
        {%- set reasoning_content = '' %}
        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
            {%- set reasoning_content = message.reasoning_content %}
        {%- else %}
            {%- if '</think>' in message.content %}
                {%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
            {%- endif %}
        {%- endif %}
        {%- if loop.index0 > ns.last_query_index %}
            {%- if loop.last or (not loop.last and reasoning_content) %}
                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
            {%- else %}
                {{- '<|im_start|>' + message.role + '\n' + content }}
            {%- endif %}
        {%- else %}
            {{- '<|im_start|>' + message.role + '\n' + content }}
        {%- endif %}
        {%- if message.tool_calls %}
            {%- for tool_call in message.tool_calls %}
                {%- if (loop.first and content) or (not loop.first) %}
                    {{- '\n' }}
                {%- endif %}
                {%- if tool_call.function %}
                    {%- set tool_call = tool_call.function %}
                {%- endif %}
                {{- '<tool_call>\n{"name": "' }}
                {{- tool_call.name }}
                {{- '", "arguments": ' }}
                {%- if tool_call.arguments is string %}
                    {{- tool_call.arguments }}
                {%- else %}
                    {{- tool_call.arguments | tojson }}
                {%- endif %}
                {{- '}\n</tool_call>' }}
            {%- endfor %}
        {%- endif %}
        {{- '<|im_end|>\n' }}
    {%- elif message.role == "tool" %}
        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
            {{- '<|im_start|>user' }}
        {%- endif %}
        {{- '\n<tool_response>\n' }}
        {{- message.content }}
        {{- '\n</tool_response>' }}
        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
            {{- '<|im_end|>\n' }}
        {%- endif %}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
    {{- '<|im_start|>assistant\n<think>\n\n</think>\n\n' }}
{%- endif %}

Please note:

• With the above chat template, the model will not think even if the user ask it to think with /think.
• The model behaviors with enable_thinking=False and /no_think are not exactly the same.
• It is not recommended to disable thinking modes completely.

[tonney007]

openai可以这样设置
client.chat.completions.create(
model="Qwen",
messages=[
{"role": "user", "content": "简单介绍一下大语言模型"}
],
extra_body={"chat_template_kwargs": {"enable_thinking": False}},
stream=True
)

[fghd-965]

Qwen3 will think before respond, similar to QwQ models. This means the model will use its reasoning abilities to enhance the quality of generated responses. The model will first generate thinking content wrapped in a ... block, followed by the final response.

Hard Switch: To strictly disable the model’s thinking behavior, aligning its functionality with the previous Qwen2.5-Instruct models, you can set enable_thinking=False when formatting the text.

text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
enable_thinking=False, # Setting enable_thinking=False disables thinking mode
)
It can be particularly useful in scenarios where disabling thinking is essential for enhancing efficiency.

Soft Switch: Qwen3 also understands the user’s instruction on its thinking behavior, in particular, the soft switch /think and /no_think. You can add them to user prompts or system messages to switch the model’s thinking mode from turn to turn. The model will follow the most recent instruction in multi-turn conversations.

[crownwang13]

u can specify a template to disable thinking through parameters when starting the VLLM service, as described in the official documentation.
https://qwen.readthedocs.io/zh-cn/latest/deployment/vllm.html

[weizaiff]

payload = {
"model": "qwen3-14b-chat",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "如何暴富"}
],
"max_tokens": 512,
"temperature": 0.7,
"top_p": 0.9,
"enable_thinking":False
}
This new para will return a no-think answer!(sorr, works in LMdeploy..)