Video · Text to video · Image to video

Kandinsky 6.0 Lite API

Kandinsky 6.0 Lite by Kandinsky Lab. Fast, low-cost open-weight text- and image-to-video with audio; 5-second clips, upscalable to 1080p or 4x.

Price
From $0.08 per run $0.026/video
Typical time
~4 min
Model id
kandinsky_6_lite

Kandinsky 6.0 Lite runs on one varg API key and one credit balance, the same as every other model here. You pay the provider's price, with no markup.

POST /v2/tools/video/call
curl -X POST https://api.varg.ai/v2/tools/video/call \
  -H "Authorization: Bearer $VARG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "kandinsky_6_lite",
  "prompt": "A street violinist plays under a bridge at night, rain on the cobblestones, the melody echoing."
}'

Kandinsky 6.0 Lite pricing

From $0.08 per run. Prices are in US dollars and are the provider's own, with no markup. Kandinsky 6.0 Lite has 2 routes: "model": "kandinsky_6_lite" picks one automatically, or pass a route key as "model" to pin it. For the exact price of a request, send the same body to POST https://api.varg.ai/v2/estimate.

  • fal $0.026/video
    fal:fal-ai/kandinsky6-lite/text-to-video

    Text to video Kandinsky 6.0 Lite text-to-video: fast, low-cost 5 s clips with audio.

    Per video
    $0.026
    Extra per num_inference_steps
    +$0.0134
    Extra when upscale_factor is 2
    +$0.16
    Extra when upscale_factor is 2.25
    +$0.16
    Extra when upscale_factor is 4
    +$0.49
    Minimum charge
    $0.08
    Most one request can cost
    $0.74
    Typical time
    ~4 min
  • fal $0.026/video
    fal:fal-ai/kandinsky6-lite/image-to-video

    Image to video Kandinsky 6.0 Lite image-to-video: fast, low-cost 5 s clips from a first frame.

    Per video
    $0.026
    Extra per num_inference_steps
    +$0.0134
    Extra when upscale_factor is 2
    +$0.16
    Extra when upscale_factor is 2.25
    +$0.16
    Extra when upscale_factor is 4
    +$0.49
    Minimum charge
    $0.08
    Most one request can cost
    $0.74
    Typical time
    ~4 min

Kandinsky 6.0 Lite inputs

The JSON body of the request. Media inputs are URLs: upload a local file with POST /v2/files and pass the URL it returns. Full JSON Schema, no key needed: api.varg.ai/v2/tools/video?model=kandinsky_6_lite

Kandinsky 6.0 Lite request fields
FieldWhat it does
model string requiredkandinsky_6_lite picks a route automatically. To pin one, pass a route key from Pricing above.
prompt string —
files array of { url } —
aspect_ratio string Allowed e.g. 16:9 | 9:16 | 1:1 | 4:3 | 3:4 | 21:9 | auto
resolution string Quality tier. Supported by this model: 480p, 1080p, 4k. Unsupported tiers fall back to the nearest available. Allowed 480p | 720p | 1080p | 4k
audio boolean Set true to generate the video with a native audio track.
duration integer Length in seconds. Not mapped by this model — ignored if sent. Allowed 1–120

Provider options

Optional, under provider_options.<provider>. Only the options of the provider that runs the job apply; pin a route to choose it.

provider_options.fal

Kandinsky 6.0 Lite options for fal
FieldWhat it does
prompt string The text prompt describing the video and its sound.
sync_mode boolean If `True`, the media will be returned as a data URI and the output data won't be available in the request history.
aspect_ratio string Allowed 16:9 | 9:16 | 1:1 | 4:3 | 3:4
generate_audio boolean Whether to generate a synchronized audio track.
upscale_factor number —
num_inference_steps integer The number of denoising steps. Lite is tuned for 10. Allowed 4–16
enable_safety_checker boolean Authorized callers may set false to request relaxed screening.
enable_prompt_expansion boolean Whether to rewrite the prompt into a detailed video+audio description with the model's own Qwen2.5-VL text encoder before generating.
image_url string (URL) The image used as the first frame of the video.

Call the Kandinsky 6.0 Lite API

POST https://api.varg.ai/v2/tools/video/call with Authorization: Bearer $VARG_API_KEY. It answers 202 with a job right away.

1. Send the request

cURL
curl -X POST https://api.varg.ai/v2/tools/video/call \
  -H "Authorization: Bearer $VARG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "kandinsky_6_lite",
  "prompt": "A street violinist plays under a bridge at night, rain on the cobblestones, the melody echoing."
}'
JavaScript
JavaScript
const headers = {
  Authorization: `Bearer ${process.env.VARG_API_KEY}`,
  'Content-Type': 'application/json',
}

const res = await fetch('https://api.varg.ai/v2/tools/video/call', {
  method: 'POST',
  headers,
  body: JSON.stringify({
    "model": "kandinsky_6_lite",
    "prompt": "A street violinist plays under a bridge at night, rain on the cobblestones, the melody echoing."
  }),
})
const job = await res.json() // { id: "job_…", status: "queued" }
Python
Python
import os
import requests

headers = {"Authorization": f"Bearer {os.environ['VARG_API_KEY']}"}

job = requests.post(
    "https://api.varg.ai/v2/tools/video/call",
    headers=headers,
    json={
      "model": "kandinsky_6_lite",
      "prompt": "A street violinist plays under a bridge at night, rain on the cobblestones, the melody echoing."
    },
).json()  # {"id": "job_…", "status": "queued"}

2. Get the result

Poll the job until its status is completed, failed or cancelled; Kandinsky 6.0 Lite typically takes about 4 min. The result is at output.outputs[0].url.

GET /v2/jobs/{id}
curl https://api.varg.ai/v2/jobs/$JOB_ID \
  -H "Authorization: Bearer $VARG_API_KEY"

# Poll until "status" is completed, failed or cancelled.
# The result is in output.outputs[0].url
JavaScript
JavaScript
let current = job
while (!['completed', 'failed', 'cancelled'].includes(current.status)) {
  await new Promise((resolve) => setTimeout(resolve, 3000))
  current = await (await fetch(`https://api.varg.ai/v2/jobs/${current.id}`, { headers })).json()
}
console.log(current.output?.outputs?.[0]?.url)
Python
Python
import time

while job["status"] not in ("completed", "failed", "cancelled"):
    time.sleep(3)
    job = requests.get(f"https://api.varg.ai/v2/jobs/{job['id']}", headers=headers).json()

print(job["output"]["outputs"][0]["url"])
Or take a webhook instead of polling

Add options.webhook_url and varg POSTs the finished job to it.

request body
{
  "model": "kandinsky_6_lite",
  "prompt": "A street violinist plays under a bridge at night, rain on the cobblestones, the melody echoing.",
  "options": {
    "webhook_url": "https://your-app.com/varg-webhook"
  }
}

From Claude, ChatGPT or Cursor (MCP)

The varg MCP server, https://mcp.varg.ai/mcp, runs Kandinsky 6.0 Lite with call_tool. Sign in with varg, no API key to paste. How to connect it

call_tool
{
  "tool": "video",
  "input": {
    "model": "kandinsky_6_lite",
    "prompt": "A street violinist plays under a bridge at night, rain on the cobblestones, the melody echoing."
  },
  "wait": true
}

Kandinsky 6.0 Lite API: questions

How much does Kandinsky 6.0 Lite cost on varg?
Kandinsky 6.0 Lite costs from $0.08 per run on varg ($0.026/video on the cheapest route). varg charges the provider's price with no markup, from one credit balance. For the exact price of a request before you run it, send the same body to POST https://api.varg.ai/v2/estimate.
How do I call the Kandinsky 6.0 Lite API?
Send POST https://api.varg.ai/v2/tools/video/call with the header "Authorization: Bearer $VARG_API_KEY" and a JSON body that includes "model": "kandinsky_6_lite". The call answers 202 with a job right away. Poll GET https://api.varg.ai/v2/jobs/{id} until "status" is "completed", then read output.outputs[0].url, or pass options.webhook_url to be called back.
Can I use Kandinsky 6.0 Lite from Claude, ChatGPT or Cursor?
Yes. Add the varg MCP server (https://mcp.varg.ai/mcp) to Claude, ChatGPT, Cursor or any other MCP client and sign in with varg, with no API key to paste. The agent runs Kandinsky 6.0 Lite with call_tool, passing tool "video" and "model": "kandinsky_6_lite".
How long does a Kandinsky 6.0 Lite request take?
Typically about 4 min on the fastest route, by the catalog's estimate. The API answers at once with a job id, so nothing waits on an open connection while it runs.

For AI agents: this page as Markdown is varg.ai/models/kandinsky_6_lite.md, and every model is listed in varg.ai/models/llms.txt.