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qwen2.5-coder-32b-instruct

Text GenerationQwen
@cf/qwen/qwen2.5-coder-32b-instruct

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings the following improvements upon CodeQwen1.5:

Model Info
Context Window32,768 tokens
LoRAYes
Unit Pricing$0.66 per M input tokens, $1.00 per M output tokens

Playground

Try out this model with Workers AI LLM Playground. It does not require any setup or authentication and an instant way to preview and test a model directly in the browser.

Launch the LLM Playground

Usage

Worker - Streaming

TypeScript
export interface Env {
AI: Ai;
}
export default {
async fetch(request, env): Promise<Response> {
const messages = [
{ role: "system", content: "You are a friendly assistant" },
{
role: "user",
content: "What is the origin of the phrase Hello, World",
},
];
const stream = await env.AI.run("@cf/qwen/qwen2.5-coder-32b-instruct", {
messages,
stream: true,
});
return new Response(stream, {
headers: { "content-type": "text/event-stream" },
});
},
} satisfies ExportedHandler<Env>;

Worker

TypeScript
export interface Env {
AI: Ai;
}
export default {
async fetch(request, env): Promise<Response> {
const messages = [
{ role: "system", content: "You are a friendly assistant" },
{
role: "user",
content: "What is the origin of the phrase Hello, World",
},
];
const response = await env.AI.run("@cf/qwen/qwen2.5-coder-32b-instruct", { messages });
return Response.json(response);
},
} satisfies ExportedHandler<Env>;

Python

Python
import os
import requests
ACCOUNT_ID = "your-account-id"
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")
prompt = "Tell me all about PEP-8"
response = requests.post(
f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/qwen/qwen2.5-coder-32b-instruct",
headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
json={
"messages": [
{"role": "system", "content": "You are a friendly assistant"},
{"role": "user", "content": prompt}
]
}
)
result = response.json()
print(result)

curl

Terminal window
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/qwen/qwen2.5-coder-32b-instruct \
-X POST \
-H "Authorization: Bearer $CLOUDFLARE_AUTH_TOKEN" \
-d '{ "messages": [{ "role": "system", "content": "You are a friendly assistant" }, { "role": "user", "content": "Why is pizza so good" }]}'

Parameters

* indicates a required field

Input

This model accepts multiple input formats. Click on the tabs below to view the parameters for each format. You can use these JSON inputs with the Workers Binding or through a fetch API call.

{
"messages": [
{ "role": "system", "content": "You are a helpful assistant" },
{ "role": "user", "content": "Tell me about Cloudflare Workers" }
]
}
  • messages * array required

    An array of message objects representing the conversation history.

    • items object

      • role * string required

        The role of the message sender (e.g., 'user', 'assistant', 'system', 'tool').

      • content * string required

        The content of the message as a string.

  • functions array

    • items object

      • name * string required

      • code * string required

  • tools array

    A list of tools available for the assistant to use.

    • items one of

      • 0 object

        • name * string required

          The name of the tool. More descriptive the better.

        • description * string required

          A brief description of what the tool does.

        • parameters * object required

          Schema defining the parameters accepted by the tool.

          • type * string required

            The type of the parameters object (usually 'object').

          • required array

            List of required parameter names.

            • items string

          • properties * object required

            Definitions of each parameter.

            • additionalProperties object

              • type * string required

                The data type of the parameter.

              • description * string required

                A description of the expected parameter.

      • 1 object

        • type * string required

          Specifies the type of tool (e.g., 'function').

        • function * object required

          Details of the function tool.

          • name * string required

            The name of the function.

          • description * string required

            A brief description of what the function does.

          • parameters * object required

            Schema defining the parameters accepted by the function.

            • type * string required

              The type of the parameters object (usually 'object').

            • required array

              List of required parameter names.

              • items string

            • properties * object required

              Definitions of each parameter.

              • additionalProperties object

                • type * string required

                  The data type of the parameter.

                • description * string required

                  A description of the expected parameter.

  • response_format object

    • type string

    • json_schema

  • raw boolean

    If true, a chat template is not applied and you must adhere to the specific model's expected formatting.

  • stream boolean

    If true, the response will be streamed back incrementally using SSE, Server Sent Events.

  • max_tokens integer default 256

    The maximum number of tokens to generate in the response.

  • temperature number default 0.6 min 0 max 5

    Controls the randomness of the output; higher values produce more random results.

  • top_p number min 0 max 2

    Adjusts the creativity of the AI's responses by controlling how many possible words it considers. Lower values make outputs more predictable; higher values allow for more varied and creative responses.

  • top_k integer min 1 max 50

    Limits the AI to choose from the top 'k' most probable words. Lower values make responses more focused; higher values introduce more variety and potential surprises.

  • seed integer min 1 max 9999999999

    Random seed for reproducibility of the generation.

  • repetition_penalty number min 0 max 2

    Penalty for repeated tokens; higher values discourage repetition.

  • frequency_penalty number min 0 max 2

    Decreases the likelihood of the model repeating the same lines verbatim.

  • presence_penalty number min 0 max 2

    Increases the likelihood of the model introducing new topics.

Output

This model returns different output formats depending on the request. Click on the tabs below to view the response structure for each format.

{
"result": {
"response": "Generated text response from the model",
"tool_calls": [],
"usage": {
"prompt_tokens": 86,
"completion_tokens": 171,
"total_tokens": 257
}
},
"success": true,
"errors": [],
"messages": []
}
  • response * string required

    The generated text response from the model

  • usage object

    Usage statistics for the inference request

    • prompt_tokens number 0

      Total number of tokens in input

    • completion_tokens number 0

      Total number of tokens in output

    • total_tokens number 0

      Total number of input and output tokens

  • tool_calls array

    An array of tool calls requests made during the response generation

    • items object

      • arguments object

        The arguments passed to be passed to the tool call request

      • name string

        The name of the tool to be called

API Schemas

The following schemas are based on JSON Schema

{
"type": "object",
"oneOf": [
{
"title": "Qwen2_5_Coder_32B_Instruct_Prompt",
"properties": {
"prompt": {
"type": "string",
"minLength": 1,
"description": "The input text prompt for the model to generate a response."
},
"lora": {
"type": "string",
"description": "Name of the LoRA (Low-Rank Adaptation) model to fine-tune the base model."
},
"response_format": {
"title": "JSON Mode",
"type": "object",
"properties": {
"type": {
"type": "string",
"enum": [
"json_object",
"json_schema"
]
},
"json_schema": {}
}
},
"raw": {
"type": "boolean",
"default": false,
"description": "If true, a chat template is not applied and you must adhere to the specific model's expected formatting."
},
"stream": {
"type": "boolean",
"default": false,
"description": "If true, the response will be streamed back incrementally using SSE, Server Sent Events."
},
"max_tokens": {
"type": "integer",
"default": 256,
"description": "The maximum number of tokens to generate in the response."
},
"temperature": {
"type": "number",
"default": 0.6,
"minimum": 0,
"maximum": 5,
"description": "Controls the randomness of the output; higher values produce more random results."
},
"top_p": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Adjusts the creativity of the AI's responses by controlling how many possible words it considers. Lower values make outputs more predictable; higher values allow for more varied and creative responses."
},
"top_k": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"description": "Limits the AI to choose from the top 'k' most probable words. Lower values make responses more focused; higher values introduce more variety and potential surprises."
},
"seed": {
"type": "integer",
"minimum": 1,
"maximum": 9999999999,
"description": "Random seed for reproducibility of the generation."
},
"repetition_penalty": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Penalty for repeated tokens; higher values discourage repetition."
},
"frequency_penalty": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Decreases the likelihood of the model repeating the same lines verbatim."
},
"presence_penalty": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Increases the likelihood of the model introducing new topics."
}
},
"required": [
"prompt"
]
},
{
"title": "Qwen2_5_Coder_32B_Instruct_Messages",
"properties": {
"messages": {
"type": "array",
"description": "An array of message objects representing the conversation history.",
"items": {
"type": "object",
"properties": {
"role": {
"type": "string",
"description": "The role of the message sender (e.g., 'user', 'assistant', 'system', 'tool')."
},
"content": {
"type": "string",
"description": "The content of the message as a string."
}
},
"required": [
"role",
"content"
]
}
},
"functions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"code": {
"type": "string"
}
},
"required": [
"name",
"code"
]
}
},
"tools": {
"type": "array",
"description": "A list of tools available for the assistant to use.",
"items": {
"type": "object",
"oneOf": [
{
"properties": {
"name": {
"type": "string",
"description": "The name of the tool. More descriptive the better."
},
"description": {
"type": "string",
"description": "A brief description of what the tool does."
},
"parameters": {
"type": "object",
"description": "Schema defining the parameters accepted by the tool.",
"properties": {
"type": {
"type": "string",
"description": "The type of the parameters object (usually 'object')."
},
"required": {
"type": "array",
"description": "List of required parameter names.",
"items": {
"type": "string"
}
},
"properties": {
"type": "object",
"description": "Definitions of each parameter.",
"additionalProperties": {
"type": "object",
"properties": {
"type": {
"type": "string",
"description": "The data type of the parameter."
},
"description": {
"type": "string",
"description": "A description of the expected parameter."
}
},
"required": [
"type",
"description"
]
}
}
},
"required": [
"type",
"properties"
]
}
},
"required": [
"name",
"description",
"parameters"
]
},
{
"properties": {
"type": {
"type": "string",
"description": "Specifies the type of tool (e.g., 'function')."
},
"function": {
"type": "object",
"description": "Details of the function tool.",
"properties": {
"name": {
"type": "string",
"description": "The name of the function."
},
"description": {
"type": "string",
"description": "A brief description of what the function does."
},
"parameters": {
"type": "object",
"description": "Schema defining the parameters accepted by the function.",
"properties": {
"type": {
"type": "string",
"description": "The type of the parameters object (usually 'object')."
},
"required": {
"type": "array",
"description": "List of required parameter names.",
"items": {
"type": "string"
}
},
"properties": {
"type": "object",
"description": "Definitions of each parameter.",
"additionalProperties": {
"type": "object",
"properties": {
"type": {
"type": "string",
"description": "The data type of the parameter."
},
"description": {
"type": "string",
"description": "A description of the expected parameter."
}
},
"required": [
"type",
"description"
]
}
}
},
"required": [
"type",
"properties"
]
}
},
"required": [
"name",
"description",
"parameters"
]
}
},
"required": [
"type",
"function"
]
}
]
}
},
"response_format": {
"title": "JSON Mode",
"type": "object",
"properties": {
"type": {
"type": "string",
"enum": [
"json_object",
"json_schema"
]
},
"json_schema": {}
}
},
"raw": {
"type": "boolean",
"default": false,
"description": "If true, a chat template is not applied and you must adhere to the specific model's expected formatting."
},
"stream": {
"type": "boolean",
"default": false,
"description": "If true, the response will be streamed back incrementally using SSE, Server Sent Events."
},
"max_tokens": {
"type": "integer",
"default": 256,
"description": "The maximum number of tokens to generate in the response."
},
"temperature": {
"type": "number",
"default": 0.6,
"minimum": 0,
"maximum": 5,
"description": "Controls the randomness of the output; higher values produce more random results."
},
"top_p": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Adjusts the creativity of the AI's responses by controlling how many possible words it considers. Lower values make outputs more predictable; higher values allow for more varied and creative responses."
},
"top_k": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"description": "Limits the AI to choose from the top 'k' most probable words. Lower values make responses more focused; higher values introduce more variety and potential surprises."
},
"seed": {
"type": "integer",
"minimum": 1,
"maximum": 9999999999,
"description": "Random seed for reproducibility of the generation."
},
"repetition_penalty": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Penalty for repeated tokens; higher values discourage repetition."
},
"frequency_penalty": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Decreases the likelihood of the model repeating the same lines verbatim."
},
"presence_penalty": {
"type": "number",
"minimum": 0,
"maximum": 2,
"description": "Increases the likelihood of the model introducing new topics."
}
},
"required": [
"messages"
]
}
]
}