Try Wan2.1 14B - Text to Video in the Workbench
Run this model interactively, tune parameters, and compare outputs.
wan-ai-wan2-1-t2v-14b-diffusers
Wan-AI/Wan2.1-T2V-14B-Diffusers is a 14B parameter Large Vision Model (LVM) designed for high-fidelity text-to-video and image-to-video generation, including support for readable text in English and Chinese within generated videos.
It excels in generating temporally consistent videos from detailed prompts, offers customizable aspect ratios, and maintains stability at both 480p and 720p resolutions across consumer-grade hardware.
Some other noteworthy features of Wan-AI/Wan2.1-T2V-14B-Diffusers include prompt enhancement for improved video quality and precision, inspiration mode for artistic visual enrichment, sound effects generation, and efficient video encoding via a variational autoencoder (VAE).
| Metric | Value |
|---|---|
| Parameter Count | 14 billion |
| Mixture of Experts | No |
| Context Length | Unknown |
| Multilingual | Yes |
| Quantized* | No |
Example request
Use the Workbench 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.
- Sync
- Async
- Async with SSE
This blocks until the video is ready (typically 5-15 minutes). Prefer Async or Async with SSE for anything beyond quick experimentation.See the video generation reference for more details.
- Minimal
- All parameters
curl -X POST https://hub.oxen.ai/api/ai/videos/generate \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OXEN_API_KEY" \
-d '{
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>"
}'
import os
import requests
response = requests.post(
"https://hub.oxen.ai/api/ai/videos/generate",
headers={
"Content-Type": "application/json",
"Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
},
json={
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>"
},
)
response.raise_for_status()
print(response.json())
curl -X POST https://hub.oxen.ai/api/ai/videos/generate \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OXEN_API_KEY" \
-d '{
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>",
"height": 480,
"width": 832,
"num_inference_steps": 16,
"num_frames": 81,
"guidance_scale": 5.0
}'
import os
import requests
response = requests.post(
"https://hub.oxen.ai/api/ai/videos/generate",
headers={
"Content-Type": "application/json",
"Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
},
json={
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>",
"height": 480,
"width": 832,
"num_inference_steps": 16,
"num_frames": 81,
"guidance_scale": 5.0
},
)
response.raise_for_status()
print(response.json())
See the async queue reference for more details.
- Minimal
- All parameters
# Enqueue, capture the generation id.
GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OXEN_API_KEY" \
-d '{
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>"
}' | jq -r '.generations[0].generation_id')
# Poll until the generation reaches a terminal status.
while true; do
STATUS=$(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 .
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": "wan-ai-wan2-1-t2v-14b-diffusers",
"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')}")
# 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 $OXEN_API_KEY" \
-d '{
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>",
"height": 480,
"width": 832,
"num_inference_steps": 16,
"num_frames": 81,
"guidance_scale": 5.0
}' | jq -r '.generations[0].generation_id')
# Poll until the generation reaches a terminal status.
while true; do
STATUS=$(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 .
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": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>",
"height": 480,
"width": 832,
"num_inference_steps": 16,
"num_frames": 81,
"guidance_scale": 5.0
},
)
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')}")
See the async queue reference for more details.
- Minimal
- All parameters
# 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": "wan-ai-wan2-1-t2v-14b-diffusers",
"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($0, 7)
if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
expect = 0
}
' | jq .
import json
import os
import requests
API_KEY = os.environ["OXEN_API_KEY"]
AUTH = {"Authorization": f"Bearer {API_KEY}"}
enqueue = requests.post(
"https://hub.oxen.ai/api/ai/queue",
headers={**AUTH, "Content-Type": "application/json"},
json={
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>"
},
)
enqueue.raise_for_status()
generation_id = enqueue.json()["generations"][0]["generation_id"]
with requests.get(
"https://hub.oxen.ai/api/events",
headers=AUTH,
stream=True,
) as stream:
event_name = None
for line in stream.iter_lines(decode_unicode=True):
if line.startswith("event: "):
event_name = line.removeprefix("event: ")
elif line.startswith("data: ") and event_name == "media_generation_completed":
payload = json.loads(line.removeprefix("data: "))
if payload.get("generation_id") == generation_id:
print(payload)
break
# Enqueue, capture the generation id.
GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OXEN_API_KEY" \
-d '{
"model": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>",
"height": 480,
"width": 832,
"num_inference_steps": 16,
"num_frames": 81,
"guidance_scale": 5.0
}' | 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 .
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": "wan-ai-wan2-1-t2v-14b-diffusers",
"prompt": "<prompt>",
"height": 480,
"width": 832,
"num_inference_steps": 16,
"num_frames": 81,
"guidance_scale": 5.0
},
)
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
Fetch model details
The models endpoint returns the full model object, including itsjson_request_schema.
curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/wan-ai-wan2-1-t2v-14b-diffusers
Request parameters
Required parameters
| Field | Type | Default | Description |
|---|---|---|---|
prompt | string | — | Prompt for generated image |
Optional parameters
| Field | Type | Default | Description |
|---|---|---|---|
height | integer | 480 | Height of the video Range: 1 – 720. |
width | integer | 832 | Width of the video Range: 1 – 1280. |
negative_prompt | string | — | Negative prompt for generated image |
num_inference_steps | integer | 16 | Number of diffusion steps to take Range: 1 – 100. |
num_frames | integer | 81 | Number of frames of video to generate Range: 1 – 120. |
guidance_scale | number | 5.0 | Guidance for generated video. Lower values can give more realistic videos. Range: 0 – 10. |
seed | integer | — | Random seed. Set for reproducible generation |