Images · Image to image
CCSR API
CCSR image upscaler. Free on provider, minimal cost.
- Typical time
- ~30 s
- Model id
ccsr
CCSR 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/image/call
curl -X POST https://api.varg.ai/v2/tools/image/call \
-H "Authorization: Bearer $VARG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "ccsr",
"files": [
{
"url": "https://example.com/input.png"
}
]
}'CCSR 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/image?model=ccsr
| Field | What it does |
|---|---|
model string required | ccsr picks a route automatically. |
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 |
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
| Field | What it does |
|---|---|
seed integer | Allowed -9007199254740991–9007199254740991 |
scale number | The scale of the output image. The higher the scale, the bigger the output image will be. Allowed 1–4 |
steps integer | The number of steps to run the model for. The higher the number the better the quality and longer it will take to generate. Allowed 10–100 |
t_max number | The ending point of uniform sampling strategy. Allowed 0–1 |
t_min number | The starting point of uniform sampling strategy. Allowed 0–1 |
tile_vae boolean | If specified, a patch-based sampling strategy will be used for VAE decoding. |
image_url string (URL) | The URL or data URI of the image to upscale. |
color_fix_type string | Allowed none | wavelet | adain |
tile_diffusion string | Allowed none | mix | gaussian |
tile_diffusion_size integer | Size of patch. Allowed 256–2048 |
tile_diffusion_stride integer | Stride of sliding patch. Allowed 128–1024 |
tile_vae_decoder_size integer | Size of VAE patch. Allowed 64–2048 |
tile_vae_encoder_size integer | Size of latent image Allowed 128–2048 |
Call the CCSR API
POST https://api.varg.ai/v2/tools/image/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/image/call \
-H "Authorization: Bearer $VARG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "ccsr",
"files": [
{
"url": "https://example.com/input.png"
}
]
}'JavaScript
JavaScript
const headers = {
Authorization: `Bearer ${process.env.VARG_API_KEY}`,
'Content-Type': 'application/json',
}
const res = await fetch('https://api.varg.ai/v2/tools/image/call', {
method: 'POST',
headers,
body: JSON.stringify({
"model": "ccsr",
"files": [
{
"url": "https://example.com/input.png"
}
]
}),
})
const job = await res.json() // { id: "job_…", status: "queued" }Python
Python
import os
import requests
headers = {"Authorization": f"Bearer {os.environ['VARG_API_KEY']}"}
job = requests.post(
"https://api.varg.ai/v2/tools/image/call",
headers=headers,
json={
"model": "ccsr",
"files": [
{
"url": "https://example.com/input.png"
}
]
},
).json() # {"id": "job_…", "status": "queued"}2. Get the result
Poll the job until its status is completed, failed or cancelled; CCSR typically takes about 30 s. The result is at output.outputs[0].url.
GET /v2/jobs/{id}
curl https://api.varg.ai/v2/jobs/$JOB_ID \
-H "Authorization: Bearer $VARG_API_KEY"
# Poll until "status" is completed, failed or cancelled.
# The result is in output.outputs[0].urlJavaScript
JavaScript
let current = job
while (!['completed', 'failed', 'cancelled'].includes(current.status)) {
await new Promise((resolve) => setTimeout(resolve, 3000))
current = await (await fetch(`https://api.varg.ai/v2/jobs/${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": "ccsr",
"files": [
{
"url": "https://example.com/input.png"
}
],
"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 CCSR with call_tool. Sign in with varg, no API key to paste. How to connect it
call_tool
{
"tool": "image",
"input": {
"model": "ccsr",
"files": [
{
"url": "https://example.com/input.png"
}
]
},
"wait": true
}CCSR API: questions
- How much does CCSR cost on varg?
- The price of a CCSR run depends on the request. 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 CCSR API?
- Send POST https://api.varg.ai/v2/tools/image/call with the header "Authorization: Bearer $VARG_API_KEY" and a JSON body that includes "model": "ccsr". 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 CCSR 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 CCSR with call_tool, passing tool "image" and "model": "ccsr".
- How long does a CCSR request take?
- Typically about 30 s 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/ccsr.md, and every model is listed in varg.ai/models/llms.txt.