Minicpm V Video

Minicpm V Video

Playground

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MiniCPM-V 4.5 is the latest, most capable MiniCPM-V model for AI video understanding and analysis. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

MiniCPM-V Video is an advanced video understanding model that analyzes video content and generates detailed descriptions, summaries, or answers to your questions. Simply upload a video and let the AI understand what’s happening on screen.


Why It Stands Out

  • Video understanding: Analyzes visual content, actions, and scenes in videos.
  • Preset prompts: Choose from ready-to-use prompts like “describe” for quick analysis.
  • Custom prompts: Ask specific questions or request particular types of analysis.
  • Affordable pricing: Get video insights at a low cost per analysis.
  • Reproducibility: Use the seed parameter to get consistent results.

Parameters

ParameterRequiredDescription
videoYesSource video (upload or public URL).
preset_promptNoPre-defined prompt type (e.g., describe & caption).
custom_promptNoYour own question or instruction about the video.
seedNoSet for reproducibility; -1 for random.
enable_sync_modeNoWait for result before returning response (API only).

How to Use

  1. Upload your video — drag and drop a file or paste a public URL.
  2. Select a preset prompt — choose “describe” or other available options for quick analysis.
  3. Add a custom prompt (optional) — ask specific questions about the video content.
  4. Click Run and wait for analysis.
  5. Review the output — get detailed descriptions or answers about your video.

Best Use Cases

  • Content Analysis — Understand what’s happening in videos without watching them.
  • Video Cataloging — Generate descriptions for video libraries and archives.
  • Accessibility — Create text descriptions of video content for accessibility purposes.
  • Content Moderation — Analyze video content for review and categorization.
  • Research & Analysis — Extract insights from video data at scale.
  • Social Media — Generate captions and descriptions for video posts.

Pricing

OutputPrice
Per video$0.015

Pro Tips for Best Quality

  • Use videos with clear visuals for more accurate analysis.
  • Use preset prompts for quick, general descriptions.
  • Use custom prompts to ask specific questions like “What objects are in this video?” or “Describe the main action.”
  • Keep videos reasonably short for faster processing.
  • Fix the seed when you need consistent results across multiple runs.

Notes

  • Ensure uploaded video URLs are publicly accessible.
  • Processing time varies based on video length and current queue load.
  • Please ensure your content complies with usage guidelines.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
  "preset_prompt": "describe",
  "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/minicpm-v/video" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
videostringYes-Video to be analyzed.
preset_promptstringNodescribedescribe, captionPreset prompt for image analysis.
custom_promptstringNo--Custom prompt for image analysis.
seedintegerNo-1-The random seed to use for the generation.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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