Topaz Starlight Precise 2.5

Try Topaz Starlight Precise 2.5 in the Workbench

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

Model ID: topazlabs-upscale-starlight-2-5-video Topaz Starlight Precise 2.5 is a video restoration and upscaling model focused on preserving fine detail and temporal consistency while improving clarity. Use this model to upscale input video to 1080p or 4k and control output frame rate.

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": "topazlabs-upscale-starlight-2-5-video",
  "input_video": "https://hub.oxen.ai/api/repos/ox/Oxen-AI-Assets/file/main/images/winter_summer_ox.mp4"
}'

curl -X POST https://hub.oxen.ai/api/ai/videos/generate \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "topazlabs-upscale-starlight-2-5-video",
  "input_video": "https://hub.oxen.ai/api/repos/ox/Oxen-AI-Assets/file/main/images/winter_summer_ox.mp4",
  "resolution": "4k",
  "enable_clc": true,
  "is_optimized_mode": true,
  "target_fps": 24
}'

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": "topazlabs-upscale-starlight-2-5-video",
  "input_video": "https://hub.oxen.ai/api/repos/ox/Oxen-AI-Assets/file/main/images/winter_summer_ox.mp4"
}' | jq -r '.generations[0].generation_id')

# Poll the single generation until it 404s (terminal state).
while curl -s -o /dev/null -w "%{http_code}" \
    -H "Authorization: Bearer $OXEN_API_KEY" \
    "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | grep -q "^200$"; do
  sleep 5
done
echo "Done. See the 'Async with SSE' tab to receive the result URL."

# 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": "topazlabs-upscale-starlight-2-5-video",
  "input_video": "https://hub.oxen.ai/api/repos/ox/Oxen-AI-Assets/file/main/images/winter_summer_ox.mp4",
  "resolution": "4k",
  "enable_clc": true,
  "is_optimized_mode": true,
  "target_fps": 24
}' | jq -r '.generations[0].generation_id')

# Poll the single generation until it 404s (terminal state).
while curl -s -o /dev/null -w "%{http_code}" \
    -H "Authorization: Bearer $OXEN_API_KEY" \
    "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | grep -q "^200$"; do
  sleep 5
done
echo "Done. See the 'Async with SSE' tab to receive the result URL."

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": "topazlabs-upscale-starlight-2-5-video",
  "input_video": "https://hub.oxen.ai/api/repos/ox/Oxen-AI-Assets/file/main/images/winter_summer_ox.mp4"
}' | 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 .

# 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": "topazlabs-upscale-starlight-2-5-video",
  "input_video": "https://hub.oxen.ai/api/repos/ox/Oxen-AI-Assets/file/main/images/winter_summer_ox.mp4",
  "resolution": "4k",
  "enable_clc": true,
  "is_optimized_mode": true,
  "target_fps": 24
}' | 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 .

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/topazlabs-upscale-starlight-2-5-video

Request parameters

Required parameters

Field	Type	Default	Description
`input_video`	`string`	—	Video file to upscale (URL or file path). Format: uri.

Optional parameters

Field	Type	Default	Description
`resolution`	`string`	`"4k"`	Target output resolution. One of: 1080p, 2k, 4k.
`creativity`	`string`	—	Controls enhancement intensity. One of: low, middle, high.
`enable_clc`	`boolean`	`true`	Enables content-aware processing.
`is_optimized_mode`	`boolean`	`true`	Enables optimization mode for faster processing.
`target_fps`	`integer`	`24`	Target frame rate (fps), up to 60. Range: 1 – 60.

Inference API

Try Topaz Starlight Precise 2.5 in the Workbench

​Example request

​Fetch model details

​Request parameters

​Required parameters

​Optional parameters

Example request

Fetch model details

Request parameters

Required parameters

Optional parameters