Kwaivgi Kling V2.6 Std Text To Video

Kwaivgi Kling V2.6 Std Text To Video

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Kling 2.6 Standard offers cost-effective text-to-video generation with smooth motion, cinematic visuals, and strong prompt adherence. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Kling V2.6 Standard is Kuaishou’s text-to-video generation model that creates high-quality videos directly from text descriptions. With support for negative prompts, multiple aspect ratios, and flexible duration, it delivers cinematic results with rich detail and natural motion.


Why Choose This?

  • Pure text-driven generation Create videos from scratch using detailed text descriptions.

  • Negative prompt support Exclude unwanted elements for more precise control over the output.

  • Multiple aspect ratios Support for 1:1, 9:16, and 16:9 to fit any platform.

  • Flexible duration Generate 5-second or 10-second videos.

  • Prompt Enhancer Built-in tool to automatically improve your video descriptions.


Parameters

ParameterRequiredDescription
promptYesText description of the video scene and motion
negative_promptNoElements to exclude from generation
aspect_ratioNoOutput ratio: 1:1, 9:16, 16:9 (default: 16:9)
durationNoVideo length: 5 or 10 seconds (default: 5)

How to Use

  1. Write your prompt — describe the scene, characters, motion, and style in detail.
  2. Add negative prompt (optional) — specify what you want to avoid in the output.
  3. Select aspect ratio — choose based on your target platform.
  4. Set duration — 5 seconds or 10 seconds.
  5. Run — submit and download your video.

Pricing

DurationCost
5s$0.21
10s$0.42

Best Use Cases

  • Social Media Content — Create short-form videos for TikTok, Reels, and Stories.
  • Concept Visualization — Bring creative ideas to life without filming.
  • Film Noir & Artistic Styles — Generate stylized footage with specific aesthetics.
  • Marketing Videos — Produce promotional content from text descriptions.
  • Storyboarding — Visualize narrative scenes for pre-production.

Pro Tips

  • Use the Prompt Enhancer to refine your descriptions automatically.
  • Be specific about style, lighting, atmosphere, and camera movement.
  • Use negative prompts to avoid common issues (e.g., “blurry, low quality, distorted”).
  • Match aspect ratio to your platform: 16:9 for YouTube, 9:16 for TikTok/Reels, 1:1 for Instagram.
  • 5s videos are more cost-effective for testing; use 10s for final production.

Notes

  • Only prompt is required; other parameters have defaults.
  • Duration options are 5 or 10 seconds only.
  • For best results, write detailed prompts with scene, motion, and style information.

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'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "aspect_ratio": "16:9",
  "duration": 5
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.6-std/text-to-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
promptstringYes-The positive prompt for the generation.
negative_promptstringNo-The negative prompt for the generation.
aspect_ratiostringNo16:91:1, 9:16, 16:9The aspect ratio of the generated media.
durationintegerNo55, 10The duration of the generated media in seconds.

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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