Wan2.1 14B - Text to Video

Generates high-fidelity, temporally consistent videos from text or images, with readable English and Chinese text, sound effects, and customizable aspect…

Try Wan2.1 14B - Text to Video in the Workbench

Run this model interactively, tune parameters, and compare outputs.

Model ID: 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

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

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

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

cURL

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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."
}'

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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."
    },
)
response.raise_for_status()
print(response.json())

All parameters

cURL

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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground.",
  "height": 480,
  "width": 832,
  "negative_prompt": " ",
  "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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground.",
        "height": 480,
        "width": 832,
        "negative_prompt": " ",
        "num_inference_steps": 16,
        "num_frames": 81,
        "guidance_scale": 5.0
    },
)
response.raise_for_status()
print(response.json())

Async

See the async queue reference for more details.

Minimal

cURL

# 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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."
}' | 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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."
    },
)
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')}")

All parameters

cURL

# 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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground.",
  "height": 480,
  "width": 832,
  "negative_prompt": " ",
  "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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground.",
        "height": 480,
        "width": 832,
        "negative_prompt": " ",
        "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')}")

Async with SSE

See the async queue reference for more details.

Minimal

cURL

# 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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."
}' | 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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."
    },
)
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

All parameters

cURL

# 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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground.",
  "height": 480,
  "width": 832,
  "negative_prompt": " ",
  "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": "A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground.",
        "height": 480,
        "width": 832,
        "negative_prompt": " ",
        "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 its json_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	"A beautiful landscape painting of a serene lake with mountains in the background and an ox in the foreground."	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