InferX Catalog | Qwen/Qwen3-32B-AWQ

Qwen/Qwen3-32B-AWQ

a 32B Qwen3 model quantized with AWQ for efficient, high-performance inference

Qwen text text2text reasoning coding chat

Log in to deploy

Qwen/Qwen3-32B-AWQ is a 32B Qwen3 model optimized with AWQ (Activation-aware Weight Quantization) to reduce GPU memory usage and improve throughput while maintaining strong reasoning, coding, and conversational capabilities, making it ideal for cost-efficient production deployments and high-concurrency workloads.

Metadata

Provider

Qwen

Modality

text

API type

text2text

Source

huggingface / Qwen/Qwen3-32B-AWQ

Created

2026-04-03 20:52:51 UTC

Updated

2026-04-13 02:59:52 UTC

Catalog version

2

Visibility

Published

Specifications

Parameters

32.00B

MoE

No

Max model length

32768

Image

vllm/vllm-openai:v0.16.0

Default Deploy Config

GPU count

1

vRAM

50000 MB

Summary

1xGPU 50000 MB

Recommended Use Cases

—

Model Spec

{
    "image": "vllm/vllm-openai:v0.16.0",
    "commands": [
        "--model",
        "Qwen/Qwen3-32B-AWQ",
        "--trust-remote-code",
        "--gpu-memory-utilization",
        "0.95",
        "--max-model-len",
        "32768"
    ],
    "resources": {
        "GPU": {
            "Count": 1,
            "vRam": 50000
        }
    },
    "envs": [],
    "policy": {
        "Obj": {
            "min_replica": 0,
            "max_replica": 1,
            "standby_per_node": 1,
            "parallel": 50,
            "queue_len": 100,
            "queue_timeout": 30.0,
            "scalein_timeout": 1.0,
            "scaleout_policy": {
                "WaitQueueRatio": {
                    "wait_ratio": 0.1
                }
            },
            "runtime_config": {
                "graph_sync": false
            }
        }
    },
    "sample_query": {
        "body": {
            "stream": "true",
            "max_tokens": "1000",
            "temperature": "0"
        },
        "path": "v1/completions",
        "prompt": "write a quick sort algorithm.",
        "apiType": "text2text",
        "dataUrl": "",
        "prompts": [],
        "loadingTimeout": 90
    }
}