If you're using remove.bg's API and your monthly bill is climbing, this guide walks you through switching to PixelAPI in about 30 minutes of work. The output format is identical (transparent PNG), the integration pattern is identical (POST image, get URL back), and the per-image cost is roughly 11× lower ($0.010 vs $0.110 on remove.bg's standard subscription).
| Metric | remove.bg | PixelAPI |
|---|---|---|
| Per-image cost (PAYG) | $0.21–$1.99 | $0.010 |
| Per-image cost (sub) | $0.11–$0.23 | $0.010 |
| Free tier | 50 preview-res / month | 100 full-res credits, no card |
| Output format | Transparent PNG | Transparent PNG (identical) |
| Latency | ~1.8s avg | ~1.9s avg |
| Quality (our 1K-image benchmark) | 40 / 45 | 38 / 45 |
| Bulk-friendly | Yes (with subscription) | Yes (no subscription) |
| GST invoice (India) | Typically no | Yes |
| Other AI tools bundled | None | 14 more (image gen, upscale, face restore, etc.) |
If you're a high-volume buyer (>1,000 images/month), the cost difference compounds. At 10,000/month, that's $1,100 vs $100 — savings of ~$1,000/month per developer integration.
Visit pixelapi.dev/app and sign up with Google or email. You get 500 free credits immediately, no credit card. Your API key is on the dashboard.
export PIXELAPI_KEY="sk_pix_xxx..."
Here's the typical remove.bg integration pattern in Python:
# Before — remove.bg
import requests
def remove_bg_old(image_path):
with open(image_path, "rb") as f:
response = requests.post(
"https://api.remove.bg/v1.0/removebg",
files={"image_file": f},
data={"size": "auto"},
headers={"X-Api-Key": REMOVE_BG_KEY},
)
if response.status_code == 200:
with open(image_path + ".no-bg.png", "wb") as out:
out.write(response.content)
else:
raise Exception(f"remove.bg error: {response.status_code} {response.text}")
Here's the equivalent PixelAPI call:
# After — PixelAPI
import requests
def remove_bg_new(image_path):
with open(image_path, "rb") as f:
response = requests.post(
"https://api.pixelapi.dev/v1/image/remove-background",
files={"image": f},
headers={"X-API-Key": PIXELAPI_KEY},
)
if response.status_code == 200:
result = response.json() # {"output_url": "https://...", "credits_used": 10}
# Download the output
out = requests.get(result["output_url"])
with open(image_path + ".no-bg.png", "wb") as f_out:
f_out.write(out.content)
else:
raise Exception(f"PixelAPI error: {response.status_code} {response.text}")
The diff is:
api.remove.bg/v1.0/removebg → api.pixelapi.dev/v1/image/remove-backgroundimage_file → imageX-Api-Key → X-API-Key (case difference)output_url + extra GET to download. (Why JSON? It carries the credits-used metadata, makes async pipelines easier, and allows proper logging without inspecting binary.)If you'd rather not hand-roll requests, the official Python SDK is even cleaner:
pip install pixelapi
from pixelapi import PixelAPI
client = PixelAPI("sk_pix_xxx...")
result = client.remove_background("photo.jpg")
result.save("photo.no-bg.png")
SDKs available for Python, JavaScript/TypeScript, Go, PHP, Ruby, and Rust on github.com/prakash-in21.
Don't migrate blind. Pick 100 images that represent your actual workload — ideally with the hard cases (hair, lace, glass, fine jewelry, fur). Run them through both APIs and compare.
import os
from pathlib import Path
from pixelapi import PixelAPI
client = PixelAPI(os.environ["PIXELAPI_KEY"])
test_images = list(Path("test_images").glob("*.jpg"))[:100]
for img in test_images:
out_path = Path("output") / f"{img.stem}.png"
out_path.parent.mkdir(exist_ok=True)
try:
result = client.remove_background(str(img))
result.save(str(out_path))
print(f"OK {img.name}: {result.credits_used} credits used")
except Exception as e:
print(f"FAIL {img.name}: {e}")
100 images costs you 1,000 credits ($1 if you're paying; free if you have signup credits left). Open the output folder, eyeball-compare to your remove.bg outputs, and decide.
Once you're satisfied with the test, the production switch is:
PIXELAPI_KEY in your secrets manager (1Password, Doppler, AWS Secrets Manager, env file).type=auto on remove.bg. PixelAPI doesn't need this parameter — it auto-detects subject. No change needed.If you process N images per month, here's the math:
| Volume / month | remove.bg sub | PixelAPI | Monthly savings |
|---|---|---|---|
| 1,000 | $110 | $10 (Starter) | $100 |
| 5,000 | $550 | $50 (Pro) | $500 |
| 10,000 | $1,100 | $50 (Pro) | $1,050 |
| 30,000 | $3,300 | $200 (Scale) | $3,100 |
| 100,000 | ~$11,000 | $200 + $0.0067/over = ~$668 | ~$10,300 |
For an Indian D2C with a 10K-photo catalog refresh per month, the savings cover a senior engineer's monthly salary.
We did a 1,000-image benchmark across 12 BG-removal APIs. PixelAPI scored 38/45 vs remove.bg's 40/45 — essentially indistinguishable on the average e-commerce shot. The 2-point gap shows up on extreme edge cases: very fine hair, complex lace, perfect-white-on-white. For the 95th percentile of e-commerce images, you won't tell the difference. Full benchmark here.
No — they're separate companies. Use up your remove.bg credits, or run dual-call for a week to confirm quality, then cut over.
BG removal is synchronous and fast (1.9s avg) — no webhook needed. For longer-running operations like 3D model generation or video processing, PixelAPI does support webhook callbacks.
99.9% uptime on the Pro and Scale tiers. Free and Starter are best-effort but the same infrastructure — you're sharing the queue, not the SLA.
You should tell them anyway, but for the legalese: PixelAPI doesn't store input images beyond 24 hours, output URLs expire after 24 hours unless you choose long-term storage, and the ToS includes standard developer-API liability terms. We're a registered Indian business with GST.
500 free credits. No credit card.
Process 100 images for free. If quality matches remove.bg, switch and save 90%+ on your monthly bill.
Get a free API key Background Removal API docsStuck on the migration? Email [email protected] with your code snippet and we'll get you unstuck.
Last updated: 2026-05-05. PixelAPI pricing is current as of this date; remove.bg pricing is from their public pricing page at the time of writing.