> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oxen.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Qwen Image 2.1

> Open 2K generation and editing, transparent output

<CardGroup cols={1}>
  <Card title="Try Qwen Image 2.1 in the Workbench" icon="flask" href="https://www.oxen.ai/ai/workbench?model=qwen-image-2-1">
    Run this model interactively, tune parameters, and compare outputs.
  </Card>
</CardGroup>

**Model ID:** `qwen-image-2-1`

Qwen Image 2.1 is the open-weight image model from Alibaba's Qwen team that folds text-to-image generation and image editing into one 7B-parameter diffusion transformer, paired with a Qwen3-VL 8B text and vision encoder.

It generates natively at 2K, 2048x2048 by default, across seven aspect ratios up to 2752x1536, and is the first Qwen image model with native transparent RGBA output, so it can produce cutouts and layered assets directly. It keeps the family's strong text rendering and identity preservation for people and products. With no input images it generates from the prompt; with up to ten reference images it edits or combines them, preserving identity and supporting local edits. Fine-tuning trains a LoRA on the text-to-image task from your own image and caption pairs.

Weights are released under the Qwen Research License, so commercial self-hosting needs a separate license from Qwen.

| Metric | Value |
| - | - |
| Parameter Count | 7B (plus 8B encoder) |
| Mixture of Experts | No |
| Max Resolution | 2752x1536 (2K) |
| Multilingual | Yes (Chinese, English) |
| Quantized\* | No |

\**Quantization is specific to the inference provider and the model may be offered with different quantization levels by other providers.*

## Example request

<Tip>
  Use the [Workbench](https://www.oxen.ai/ai/workbench?model=qwen-image-2-1) as a request builder: configure parameters for this model in the UI, then open the **API** tab to copy the exact cURL or Python call.
</Tip>

<Tabs>
  <Tab title="Sync">
    See the [image editing reference](/inference-api/reference/image_editing) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          curl -X POST https://hub.oxen.ai/api/ai/images/edit \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>"
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>"
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Basic parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          curl -X POST https://hub.oxen.ai/api/ai/images/edit \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>",
            "input_images": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ]
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>",
                  "input_images": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ]
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          curl -X POST https://hub.oxen.ai/api/ai/images/edit \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>",
            "input_images": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9",
            "resolution": "2K",
            "guidance_scale": 1,
            "output_format": "png"
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>",
                  "input_images": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9",
                  "resolution": "2K",
                  "guidance_scale": 1,
                  "output_format": "png"
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Async">
    See the [async queue reference](/inference-api/reference/async_queue) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>"
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Basic parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>",
            "input_images": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ]
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>",
                  "input_images": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ]
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>",
            "input_images": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9",
            "resolution": "2K",
            "guidance_scale": 1,
            "output_format": "png"
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>",
                  "input_images": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9",
                  "resolution": "2K",
                  "guidance_scale": 1,
                  "output_format": "png"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Async with SSE">
    See the [async queue reference](/inference-api/reference/async_queue) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>"
          }' | jq -r '.generations[0].generation_id')

          # Stream the SSE channel, grab the data line that follows a
          # media_generation_completed event for our id, and pretty-print it.
          curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
            | awk -v id="$GEN_ID" '
              /^event: media_generation_completed$/ { expect=1; next }
              /^data: / && expect {
                payload = substr($0, 7)
                if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
                expect = 0
              }
            ' | jq .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Basic parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>",
            "input_images": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ]
          }' | jq -r '.generations[0].generation_id')

          # Stream the SSE channel, grab the data line that follows a
          # media_generation_completed event for our id, and pretty-print it.
          curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
            | awk -v id="$GEN_ID" '
              /^event: media_generation_completed$/ { expect=1; next }
              /^data: / && expect {
                payload = substr($0, 7)
                if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
                expect = 0
              }
            ' | jq .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>",
                  "input_images": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ]
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "qwen-image-2-1",
            "prompt": "<prompt>",
            "input_images": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9",
            "resolution": "2K",
            "guidance_scale": 1,
            "output_format": "png"
          }' | jq -r '.generations[0].generation_id')

          # Stream the SSE channel, grab the data line that follows a
          # media_generation_completed event for our id, and pretty-print it.
          curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
            | awk -v id="$GEN_ID" '
              /^event: media_generation_completed$/ { expect=1; next }
              /^data: / && expect {
                payload = substr($0, 7)
                if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
                expect = 0
              }
            ' | jq .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "qwen-image-2-1",
                  "prompt": "<prompt>",
                  "input_images": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9",
                  "resolution": "2K",
                  "guidance_scale": 1,
                  "output_format": "png"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>
</Tabs>

## Fetch model details

The [models endpoint](/inference-api/reference/models/overview) returns the full model object, including its `json_request_schema`.

```bash theme={null}
curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/qwen-image-2-1
```

## Request parameters

### Required parameters

| Field | Type | Default | Description |
| - | - | - | - |
| `prompt` | `string` | — | Text prompt describing the image to generate, or the edit to apply. Use @Image1, @Image2, etc. to reference the input images. Ask for a transparent background to get an RGBA cutout. |

### Optional parameters

| Field | Type | Default | Description |
| - | - | - | - |
| `input_images` | `array<string>` | — | Optional reference images to edit or combine, in order. Reference them in the prompt as @Image1, @Image2, etc. Up to 10 images. |
| `aspect_ratio` | `string` | `"16:9"` | Aspect Ratio One of: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3. |
| `resolution` | `string` | `"2K"` | Resolution One of: 1K, 2K. |
| `guidance_scale` | `number` | `1` | Classifier-free guidance strength, 1 to 10. 1 is the provider default with no guidance; raise it for sharper, more literal results. The negative prompt only applies above 1. Range: 1 – 10. |
| `negative_prompt` | `string` | — | What to keep out of the image. Only applies when guidance scale is above 1. |
| `image_size` | `object` | — | Pixel dimensions sent to fal, derived from aspect\_ratio and resolution. |
| `output_format` | `string` | `"png"` | Output format. PNG and WebP preserve transparency; JPEG fills it with white. One of: png, jpeg, webp. |


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