Irmu vs ZenRows
Two similar credit-based platforms — the difference is agent tooling versus browser and proxy depth.
ZenRows has spent the last two years building toward AI agents. Its product is organised around four primitives — Fetch, Extract, Browser and Sessions or Batch — that share one credit pool, and it ships an MCP server, agent skills and workflow tooling on top. If your consumer is an agent rather than a pipeline, that surface is well thought through.
Irmu's shape is similar enough that the comparison comes down to details: both are credit-based, both share the pool across products, both expose residential IPs and rendering as priced options. Irmu's advantages are a published multiplier table, geotargeting down to city level at no extra cost, and an HTTP proxy port for code you are not going to rewrite.
One caveat on pricing: ZenRows publishes its plans through a credit slider rather than fixed named tiers, and the entry price was not readable as a plain figure on the pages we checked. Confirm it against their pricing page before you model spend.
What each one costs
Public list pricing, checked on 29 August 2026. Vendors change plans often — verify on their pricing page before you commit.
Irmu
$40 / month — 200,000 credits
Credits, one ledger for every API. Plain fetch is 1 credit, JavaScript rendering 5, premium residential 10, premium plus rendering 25, an AI extraction query 5, and geotargeting by country, region or city is free. A response from the target — including 404, 500 or an anti-bot block — is a successful request and is billed. Requests Irmu cannot serve for its own internal reasons, or to domains outside coverage such as .gov, are not billed.
ZenRows
Credit-slider plans starting at roughly 120,000 credits per month — exact entry price not published as a plain figure
Credits shared across Fetch, Extract, Browser and Sessions, with published cost multipliers and pay-per-success billing. Premium residential proxies are a paid add-on layer.
- ZenRows' entry-tier price and free-tier size were not readable as plain figures on their pricing page when we checked, so treat any quoted number as provisional and verify directly.
- Both platforms share one credit pool across products, which makes per-page cost the only meaningful comparison — run the same sample through each.
- ZenRows describes pay-per-success billing without publishing the exact success definition we could quote. Irmu states its definition plainly: a response from the target is billed; Irmu-side failures and uncovered domains such as .gov are not.
Side by side
| Capability | Irmu | ZenRows |
|---|---|---|
| Shared credit pool across products | Yes | Yes |
| Published multiplier table | 1 / 5 / 10 / 25, synced daily on this site | Published in docs across primitives |
| Residential IPs | Premium tier at 10 credits, 25 with rendering | Premium Proxy add-on layer |
| Browser sessions | Browser endpoint with clicks, waits and scrolls | Browser and Sessions primitives |
| Agent tooling | llms.txt, markdown docs mirrors, agent rules files | MCP server, agent skills, plugins, workflows |
| HTTP proxy port | Not available yet — use GET /crawl | Premium proxy endpoint |
| Geotargeting | Country, region and city at no extra cost | Geotargeting on premium proxies |
| AI extraction | 5 credits, or free with your own model | Extract primitive, credit-priced |
Which one fits your job
Choose ZenRows when
- You are building agents and want an MCP server and skills that already exist.
- Their four-primitive model maps directly onto how you have structured your own pipeline.
- You want workflow tooling inside the vendor rather than in your own orchestrator.
- Their anti-bot handling has already been validated against your hardest target.
Choose Irmu when
- You want the credit table visible and versioned rather than assembled from several doc pages.
- City and region geotargeting are part of the requirement and you do not want them priced as an add-on.
- You need to point your own language model at pages and pay nothing per extraction query.
- Existing code should route through a proxy port unchanged rather than be rewritten as API calls.
What ZenRows does well
- MCP server and agent tooling as first-party products
- Clean four-primitive product model on one credit pool
- Pay-per-success billing
- Strong anti-bot bypass reputation
If agents are your primary consumer and MCP support decides the evaluation, ZenRows has the head start. If you want published pricing arithmetic, free geotargeting at city level and a proxy port for legacy code, Irmu is the closer fit.
The same request, both ways
Both accept the target URL and options as query parameters, so a switch is typically the base URL and a couple of flag names.
ZenRows
import requests
r = requests.get(
"https://api.zenrows.com/v1/",
params={
"apikey": ZENROWS_KEY,
"url": "https://example.com/product/42",
"js_render": "true",
"premium_proxy": "true",
"proxy_country": "us",
},
timeout=90,
)
html = r.textIrmu
import requests
r = requests.get(
"https://app.irmu.com/api/crawl",
params={
"url": "https://example.com/product/42",
"js": "true",
"premium": "true",
"country": "us",
},
headers={"Authorization": f"Bearer {IRMU_KEY}"},
timeout=90,
)
r.raise_for_status()
html = r.textSwitching questions
Other comparisons
Irmu vs Firecrawl
Agent-ready markdown and crawling versus a full fetch, browser, screenshot and proxy stack.
Irmu vs ScrapingBee
A closely matched credit model — the difference is browser control and the proxy port.
Irmu vs ScrapingDog
Similar entry pricing — the split is dedicated site scrapers versus general-purpose access.
Irmu vs ScraperAPI
Structured e-commerce endpoints and no-code pipelines versus a general access layer.
Irmu vs Bright Data
The largest proxy network in the market versus a simpler, credit-priced access layer.
Irmu vs Apify
A marketplace of pre-built Actors versus a direct API you call from your own code.
Irmu vs Oxylabs
Per-target enterprise pricing and strict pay-for-success versus a single credit ledger.
Try Irmu alongside ZenRows
200 free credits every month, no card required — benchmark on your own targets.