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Qwen3 32B AWQ is the latest large language model in the Qwen series, offering advancements in reasoning, instruction-following, agent capabilities, and multilingual support. It uses AWQ quantization for efficient inference while maintaining high quality.

Try in playground

Test Qwen3 32B AWQ in the Runpod Hub playground.
Endpointhttps://api.runpod.ai/v2/qwen3-32b-awq/runsync
Pricing$10.00 per 1M tokens
TypeText generation
This endpoint is fully compatible with the OpenAI API. See the OpenAI compatibility examples below.

​
Request

All parameters are passed within the input object in the request body.
​
input.prompt
string
required
Prompt for text generation.
​
input.max_tokens
integer
default:"512"
Maximum number of tokens to output.
​
input.temperature
float
default:"0.7"
Randomness of the output. Lower values make output more predictable and deterministic. Range: 0.0-1.0.
​
input.top_p
float
Nucleus sampling threshold. Samples from the smallest set of words whose cumulative probability exceeds this threshold.
​
input.top_k
integer
Restricts sampling to the top K most probable words.
​
input.stop
string
Stops generation if the given string is encountered.
curl -X POST "https://api.runpod.ai/v2/qwen3-32b-awq/runsync" \
  -H "Authorization: Bearer $RUNPOD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": {
      "prompt": "Write a Python function that checks if a number is prime:",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }'

​
Response

​
id
string
Unique identifier for the request.
​
status
string
Request status. Returns COMPLETED on success, FAILED on error.
​
delayTime
integer
Time in milliseconds the request spent in queue before processing began.
​
executionTime
integer
Time in milliseconds the model took to generate the response.
​
workerId
string
Identifier of the worker that processed the request.
​
output
object
The generation result containing the text and usage information.
​
output.choices
array
Array containing the generated text.
​
output.cost
float
Cost of the generation in USD.
​
output.usage
object
Token usage information with input and output counts.
{
  "delayTime": 25,
  "executionTime": 3153,
  "id": "sync-0f3288b5-58e8-46fd-ba73-53945f5e8982-u2",
  "output": [
    {
      "choices": [
        {
          "tokens": [
            "def is_prime(n):\n    if n <= 1:\n        return False\n    for i in range(2, int(n**0.5) + 1):\n        if n % i == 0:\n            return False\n    return True"
          ]
        }
      ],
      "cost": 0.0001,
      "usage": {
        "input": 10,
        "output": 100
      }
    }
  ],
  "status": "COMPLETED",
  "workerId": "pkej0t9bbyjrgy"
}

​
OpenAI API compatibility

Qwen3 32B AWQ is fully compatible with the OpenAI API format. You can use the OpenAI Python client to interact with this endpoint.
Python (OpenAI SDK)
from openai import OpenAI

client = OpenAI(
    api_key=RUNPOD_API_KEY,
    base_url="https://api.runpod.ai/v2/qwen3-32b-awq/openai/v1",
)

response = client.chat.completions.create(
    model="Qwen/Qwen3-32B-AWQ",
    messages=[
        {
            "role": "system",
            "content": "You are a helpful coding assistant.",
        },
        {
            "role": "user",
            "content": "Write a Python function that checks if a number is prime.",
        },
    ],
    max_tokens=525,
)

print(response.choices[0].message.content)
For streaming responses, add stream=True:
Python (Streaming)
response = client.chat.completions.create(
    model="Qwen/Qwen3-32B-AWQ",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms."}
    ],
    max_tokens=525,
    stream=True,
)

for chunk in response:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")
For more details, see Send vLLM requests and the OpenAI API compatibility guide.

​
Cost calculation

Qwen3 32B AWQ charges $10.00 per 1M tokens. Example costs:
TokensCost
1,000 tokens$0.01
10,000 tokens$0.10
100,000 tokens$1.00
1,000,000 tokens$10.00