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TrustpilotConcurrency, often called threads, is the number of connections or requests you run through your proxies at the same time. It sets how fast a job finishes and how much load lands on each IP and each target site.
Each open request occupies one slot until the response arrives. Throughput is roughly concurrency divided by response time: 20 parallel requests that each take half a second give about 40 requests per second. Doubling the threads doubles throughput only until something else limits it, such as your bandwidth, CPU, the proxy or the target site.
Threads, processes and async tasks are all ways to reach the same goal. A Python ThreadPoolExecutor, an asyncio client or a Node.js script with a promise pool each keep a fixed number of requests in flight. Async clients handle hundreds of open connections with little memory; browser automation needs far more resources per slot.
Some providers cap threads per account or per IP. Others leave it open and let the target site's limits decide. Know which applies before you size a job, because a cap on the proxy side shows up as queued or refused connections, not as slow responses.
import concurrent.futures
import requests
PROXY = "http://USER:PASS@HOST:PORT"
proxies = {"http": PROXY, "https": PROXY}
urls = [f"https://example.com/page/{i}" for i in range(1, 51)]
def fetch(url):
r = requests.get(url, proxies=proxies, timeout=30)
return url, r.status_code
with concurrent.futures.ThreadPoolExecutor(max_workers=10) as pool:
for url, status in pool.map(fetch, urls):
print(status, url)The number that matters to a website is requests per IP per second, not your total thread count. Running 200 threads through 200 IPs looks like 200 ordinary visitors; running 200 threads through 2 IPs looks like two very busy machines and soon meets rate limiting, shown as HTTP 429 responses.
How many proxies do I need? works through the sizing step by step. CleanProxies static ISP proxies have unlimited threads and unlimited bandwidth, so your concurrency is limited only by your own setup and the sites you visit.
The CleanProxies proxy that fits best here, with a $4.99 trial to test it first.
Dedicated IPs on US carrier ASNs with unlimited bandwidth and threads, never shared.
Dedicated static IPs registered to US and Canadian ISPs. The address stays the same for as long as you hold it, with unlimited bandwidth and HTTP(S) or SOCKS5 access.
Setup guides and best practices from the CleanProxies blog.
Shared vs dedicated ISP proxies explained: what each model means, what providers publish about sharing, when shared is enough, cost per successful request, and a tested Python script to audit your proxy list.
A step-by-step guide to testing proxy quality before you use it: connectivity, exit IP, ASN, blacklists, fraud score, speed and WebRTC/DNS leaks, with free tools, cURL commands and what good results look like.
Oxylabs' best rates need a $2,500/month enterprise plan. We priced five workloads on Oxylabs and five alternatives on 1 November 2026, with screenshots. CleanProxies ranks #1: dedicated US ISP proxies as low as $0.75/IP, residential from $0.63/GB that never expires.
Smartproxy is now Decodo. We priced the same workloads on Decodo and six alternatives on 1 November 2026, with screenshots. CleanProxies ranks #1: residential as low as $0.63/GB that never expires, US ISP proxies as low as $0.75/IP, mobile from $0.79/GB.
The best IPRoyal alternatives in 2026, compared on prices read from each provider's pricing page on 31 October with screenshots. CleanProxies ranks #1: residential as low as $0.63/GB that never expires, US ISP proxies as low as $0.75/IP with unlimited bandwidth, mobile from $0.79/GB.
A /24 subnet has 256 IPv4 addresses: 254 usable on a LAN, 251 in AWS or Azure, and 255 dedicated proxy IPs per block at CleanProxies. CIDR cheat sheet, Python examples and a tested script that audits your proxy list by /24.
Terms that come up alongside Concurrency.
Straight answers about Concurrency.
Threads is the number of requests or connections you run at the same time. More threads finish a job faster but put more load on each IP and each target site.
