SparkProxy vs Smartproxy (Decodo): Which to Choose

Decodo is the broader platform. It sells residential, static residential (ISP), mobile, and datacenter proxies plus several scraping products, and its residential network is in a size class SparkProxy does not operate in. If your work needs residential or mobile exit IPs, sub-country targeting, or one vendor covering every proxy type, Decodo wins and this comparison is short.

SparkProxy is narrower on purpose: rotating datacenter proxies billed by concurrent threads with unlimited bandwidth, plus a managed Scraping API billed in credits. If your targets tolerate datacenter IPs and your problem is a bill that moves with traffic volume, the flat model is the reason to look.

The uncomfortable part is that neither vendor's pricing page can be read against the other's directly. Decodo meters gigabytes, IPs, and thousands of requests. SparkProxy meters threads and credits. Section 9 gives you the arithmetic to collapse both into one number.

Smartproxy rebranded as Decodo in 2025. The company's site states plainly that "Smartproxy is now Decodo" and describes it as "the same trusted team and solutions you've relied on since 2018," presenting the change as a move from proxy infrastructure to a broader data platform. Existing accounts carried over.

Practically, any Smartproxy price in an older review is stale by definition, and review sites still indexing under the old name are why you see both names on one results page. For the rest of this article we say Decodo, since that is the name on the pricing pages we quote.

Decodo lists five proxy categories on its homepage as of August 2026: residential, static residential (ISP), mobile, datacenter, and a Site Unblocker, alongside a Web Scraping API, a Fast Search API, a video downloader, an AI parser, and an MCP server. The homepage advertises "125M+" IPs across "195+ locations." Each product carries its own pricing model, precise for large buyers and a lot to read for small ones.

SparkProxy sells two things: premium rotating datacenter proxies on flat monthly plans with unlimited bandwidth, and a Scraping API that wraps proxy selection, rotation, headless Chrome rendering, and anti-bot handling behind one endpoint. SparkProxy publishes over 1 million premium datacenter IPs across 80+ countries, 99.9% uptime, and 1 Gbps ports. There is no separately sold residential, ISP, or mobile product.

If you have not settled which proxy category your project needs, decide that first. Our breakdown of residential vs datacenter proxies covers the trade, and picking the wrong category costs more than picking the wrong provider inside it.

Competitor figures below are taken from Decodo's own product and pricing pages as viewed in August 2026. Vendor pricing, pool sizes, and plan structures change often, sometimes monthly. Verify both vendors' current pages before you buy anything based on this table.

One row deserves a pause. Decodo's datacenter material carries a "100K+ rotating & static shared IPs" line and a "500K+ IP Datacenter Pool" line in different places on the same product area. Both are the vendor's own marketing, and we will not pretend to know which is operative. Treat every advertised pool figure, ours included, as a marketing claim until you count distinct exit IPs yourself during a trial.

Most proxy comparison articles rank vendors by pool size and headline price. Both are close to useless here, because the two companies charge for different things.

Decodo's dominant unit is consumption. Residential and mobile are per gigabyte, datacenter is per gigabyte or per IP, and the Web Scraping API is per thousand requests at a rate that varies by proxy type and whether JavaScript rendering is on. Your bill moves with what you pull.

SparkProxy's unit is capacity. Datacenter plans sell a thread count against a rotating pool, and the Scraping API sells credits. Inside a datacenter plan, a month where you transfer 300 GB costs the same as a month where you transfer 30 GB.

Neither is better in the abstract. They fail in opposite directions.

Consumption billing is precise. You attribute cost to a project or a team, and pay nothing for idle capacity. It punishes you when a target starts serving heavier pages, when a retry storm follows an outage, or when someone forgets to block images in a headless browser. We have watched a per-GB bill triple because a target swapped a JSON endpoint for a rendered page.

Capacity billing is predictable. The number goes in a budget and stays there. It punishes you when usage is spiky or small, because you pay for the ceiling whether or not you touch it. A team pulling 4 GB a month is wasting money on a flat plan.

So the real question is not who is cheaper. It is: does your bill need to be accurate, or does it need to be stable? If per-project cost attribution matters more than the total, consumption billing is correct and Decodo is built for it. If a surprise invoice is what hurts, capacity billing is correct. Our walkthrough of datacenter proxy pricing models shows the arithmetic on both sides.

This is the one category where the two products genuinely overlap.

SparkProxy's datacenter ladder is flat and published: $75/month for 100 threads, $140 for 250, $240 for 500, and $440 for 1,000, all with unlimited bandwidth and IP whitelist or user:pass authentication. There is no gigabyte meter and no per-IP line item.

Decodo's datacenter pricing page, as of August 2026, lists three models: pay per GB with unlimited IPs, on tiers running from $0.60/GB at 10 GB down to $0.45/GB at 1,000 GB; pay per IP from $0.10/IP; and dedicated IPs from $2.50/IP with unlimited traffic. The page also advertises 99.99% uptime and a sub-0.3-second response time, which are vendor marketing claims rather than anything we measured.

The comparison that matters is a bytes-per-record calculation, not a price sticker. Crawl 500,000 product pages a month at roughly 1.5 MB per rendered page and you move about 750 GB. On Decodo's listed per-GB tiers, 750 GB sits between the 500 GB and 1,000 GB rows, so in the region of $340 to $360 at list. The same crawl fits inside SparkProxy's $240 Boost plan at 500 threads, and costs $240 whether those pages weigh 1.5 MB or 4 MB.

Now flip the profile. Hit a JSON API returning 8 KB per record, 200,000 records a month, and you move roughly 1.6 GB. Decodo's per-GB model bills a few dollars. Any flat plan bills the plan price. Flat billing is the wrong choice for that workload, and we will say so rather than dress it up.

The dividing line is data volume per useful record, and it is not subtle. Heavy rendered pages, images, PDFs, and downloads favor flat unmetered plans. Lean JSON and text endpoints favor per-GB. If you need fixed identities rather than rotation, neither applies and you want dedicated IPs, which Decodo sells and SparkProxy does not; shared vs dedicated datacenter proxies covers that trade, and understanding concurrent connections in proxies covers sizing a thread count against your real request rate.

Short section, because there is no contest.

Decodo's residential pricing page advertises 115M+ IPs across 195+ locations with continent, country, state, city, ZIP, and ASN targeting, and lists subscription tiers from $3.75/GB at 3 GB down to $2.75/GB at 100 GB, with pay as you go at $4/GB. The same page advertises a 99.92% success rate, 99.99% uptime, and a sub-0.5-second average response time. Those are the vendor's published marketing figures, not measurements we ran, so test them on your own targets before treating them as guarantees. Third-party benchmark outlets have also ranked Decodo's residential network near the top for response time; one benchmark is one data point, not a fact about your workload.

SparkProxy does not sell a standalone residential product. Its Scraping API routes through a premium pool for harder targets rather than exposing residential IPs for you to manage. Mobile and ISP proxies, listed on Decodo's homepage from $2.25/GB and $0.27/IP, are not in the SparkProxy catalog at all.

If your target hard-blocks datacenter ASNs, or your work is social media automation, mobile app testing, or ad verification needing carrier IPs, buy from Decodo or another residential specialist. No amount of datacenter tuning changes that.

Both companies sell a managed scraping endpoint, and both hide the real price behind a different unit. Here is the conversion, which is the part most comparison articles skip.

SparkProxy's Scraping API charges credits per request: 1 for a rotating-proxy fetch without JavaScript, 5 with rendering, 10 for a premium proxy without JS, and 25 for premium with JS. Add-ons cost 5 credits each: stealth mode, country targeting, a custom JS scenario, and screenshot or PDF output. A basic call:

curl -H "X-API-Key: YOUR_API_KEY" \
  "https://scrape.sparkproxy.io/api/v1?url=https://www.sparkproxy.io/&render_js=false&format=md"

Note render_js=false there. Rendering is on by default, so an unmodified call costs 5 credits rather than 1. That one parameter is the difference between $0.10 and $0.50 per thousand requests on the Growth plan, and it is the most common budgeting mistake we see.

Reconciling spend from your own logs is easy, because every plain response carries the cost in headers:

import requests

resp = requests.get(
    "https://scrape.sparkproxy.io/api/v1",
    headers={"X-API-Key": "YOUR_API_KEY"},
    params={
        "url": "https://www.sparkproxy.io/blog/",
        "render_js": "true",   # real headless Chrome, 5 credits
        "format": "md",        # clean Markdown instead of raw HTML
        "tag": "price-crawl",  # label requests for later accounting
    },
    timeout=90,
)
resp.raise_for_status()

print(resp.headers["X-Job-Id"],
      resp.headers["X-Credits-Used"],
      resp.headers["X-Duration-Ms"])

Now divide plan price by credits to get a price per credit, then multiply by the credit cost of your actual request shape. On the $99 Growth plan at 1M credits, one credit is $0.000099:

Decodo publishes its own per-1,000-request rates. As of August 2026 its scraping page lists standard proxies at $0.50 per 1K requests, standard plus JavaScript rendering at $0.75, premium proxies at $1.00, and premium plus JS at $1.50, with paid plans advertised at $19, $49, and $99 per month and a free tier of 2K requests. Those allowances imply the effective rate falls as you scale: the $99 tier is advertised at 707K standard requests, which works out near $0.14 per thousand by their own published numbers.

Read that comparison carefully, because it cuts both ways. On plain and JS-rendered fetches through standard rotating proxies, SparkProxy's credit math lands cheaper at the $99 tier. On premium and residential-backed requests, Decodo's advertised rate is materially cheaper than ours, which is what you would expect from the vendor that owns a 115M+ IP residential network. If most of your traffic needs premium exits, Decodo is likely the cheaper platform.

Both vendors will change these numbers. Do the division yourself, on the day you buy, against the request shape you actually send. For the wider question of whether to buy a managed API at all, see web scraping API vs self-managed proxies.

Price per gigabyte, price per IP, price per thousand requests, and price per credit are four incompatible units. Exactly one number compares them, and almost nobody calculates it: cost per 1,000 successfully extracted records.

Success rate is part of the price. A provider at half the unit cost that fails 30% of your requests is not half the cost, because you pay for the retries, and on consumption billing you pay for the bytes those retries pulled too.

Here is the calculation as a script. Run it with your own numbers after a trial on your real targets, not on a benchmark site.

def per_1k_records(monthly_cost, records_per_month):
    """One comparable number across any billing unit."""
    return monthly_cost / (records_per_month / 1000)

def flat_plan(plan_price, requests_needed, success_rate, records_per_request=1):
    # Capacity billing: retries cost time, not money.
    records = requests_needed * success_rate * records_per_request
    return plan_price, records

def per_gb_plan(price_per_gb, requests_needed, mb_per_request, success_rate,
                records_per_request=1):
    # Consumption billing: failed requests still move bytes and still bill.
    gb = (requests_needed * mb_per_request) / 1024
    records = requests_needed * success_rate * records_per_request
    return gb * price_per_gb, records

def per_1k_req_plan(price_per_1k, requests_needed, success_rate,
                    records_per_request=1):
    records = requests_needed * success_rate * records_per_request
    return (requests_needed / 1000) * price_per_1k, records

REQS, SUCCESS, MB = 500_000, 0.94, 1.5

cost_a, rec_a = flat_plan(240, REQS, SUCCESS)
cost_b, rec_b = per_gb_plan(0.48, REQS, MB, SUCCESS)
cost_c, rec_c = per_1k_req_plan(0.50, REQS, SUCCESS)

for name, cost, rec in (("flat threads", cost_a, rec_a),
                        ("per GB", cost_b, rec_b),
                        ("per 1K requests", cost_c, rec_c)):
    print(f"{name:16} ${cost:8.2f}  ${per_1k_records(cost, rec):.3f} / 1K records")

Three things that script makes visible, which no pricing page will.

Failed requests are free on capacity billing and billed on consumption billing. At a 94% success rate you pay for 30,000 wasted requests per 500,000 on a per-GB or per-request plan, and nothing extra on a thread plan.

Bytes per request dominates per-GB models completely. Change MB from 1.5 to 0.2 and the per-GB option wins outright. That one variable, not the vendor, decides the outcome.

Records per request is the lever most teams never pull. Scrape a paginated listing carrying 40 records instead of 40 detail pages and every cost model drops by an order of magnitude. Fixing your crawl shape beats switching vendors, most of the time.

Decodo advertises a free Web Scraping API tier at 2K requests with no card, a 3-day 100 MB residential trial, and a 14-day money-back window on paid plans, per its pricing pages in August 2026. That free tier is genuinely good, and its $19/month entry plan undercuts SparkProxy's $49 Scraping API tier. SparkProxy gives a 3-day datacenter trial with 250 threads and no card, plus 1,000 free Scraping API credits, authenticated by IP whitelist or user:pass. There is less to configure here, mostly because there is less product. Residential access at any reputable vendor may also involve a know-your-customer step, which is appropriate given how those networks are sourced.

Pick Decodo when:

• You need residential or mobile IPs. SparkProxy does not sell them standalone, so this is not close.
• You need targeting below country level: city, state, ZIP, or ASN. SparkProxy targets by country.
• Most of your API traffic needs premium or residential-backed exits, where Decodo's advertised per-1K rate beats SparkProxy's credit math.
• Your workload is data-light, a few KB per record, where per-GB billing costs less than any flat plan.
• You want a free tier and a low entry price to validate an idea before committing.
• You need fixed dedicated IPs for session-bound or allowlisted work.
• You want one vendor and one invoice across residential, ISP, mobile, datacenter, and unblocking.
• You want pre-built parsers and templates rather than writing extraction rules yourself.

If two or more of those describe your project, Decodo is the better buy.

Pick SparkProxy when:

• Your targets are datacenter-friendly: product catalogs, SERPs, price monitoring, rank tracking, public research data.
• Your workload is bandwidth-heavy, with rendered pages, images, or downloads that would run up a gigabyte meter.
• Your constraint is per-IP rate limiting, where many rotating identities beat a rented set of addresses.
• You need a fixed monthly number you can budget without forecasting consumption.
• Your success rate sits below 95% on a hard target, so retries are frequent and you would rather not pay for them twice.
• You are a developer or small team who wants published pricing and one endpoint instead of a product matrix.

Before committing either way, our checklist on what to evaluate when selecting a proxy service puts these criteria in a sensible order.

Skip the feature matrix. Run four measurements against your real targets using both free trials.

Measure the datacenter block rate. Send 200 requests through a datacenter proxy and count successes. Blocked immediately regardless of headers and fingerprint means you need residential, and Decodo is your answer. A low block rate means you have a real choice.

Measure bytes per request. Log Content-Length for 100 pages and take the median. Under roughly 200 KB, consumption billing tends to win. Over about 1 MB, flat capacity billing tends to win, and the gap widens fast.

Measure your success rate. Recompute both options at that rate with the script above. This step flips outcomes, because retries are billed on one model and free on the other.

Measure records per request. If the number is 1, look for a listing page or an underlying API that raises it before shopping for a vendor at all.

Four numbers, one afternoon, and both trials cost nothing. That beats any comparison table, including the one above. These are also not mutually exclusive: plenty of teams run high-volume datacenter-friendly targets on a flat plan and keep a residential account open for the sites that reject datacenter ranges.