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Best Proxies for AI 2026

A comparison of proxy providers for AI agents, LLM data pipelines, and machine-learning data collection in 2026.

Updated 2026 · 9 providers ranked

AI agents, LLM data pipelines, and automated research workflows put different demands on proxy infrastructure than classic scraping: longer-lived sessions, bursty parallel requests, and bandwidth-heavy collection runs. This guide evaluates nine providers against those requirements using a consistent set of criteria.

Top 9 Providers Ranked

1

Hex Proxies

9/10

Pros

  • Dedicated US ISP IPs (Ashburn VA, New York, San Francisco)
  • Unlimited ISP bandwidth with flat per-IP pricing
  • $5 24-hour trial
  • No minimum commitment

Cons

  • Smaller product catalog
  • Newer market entrant
  • US-only ISP coverage

Best for: AI agents and bandwidth-heavy pipelines that benefit from dedicated US ISP IPs with flat per-IP billing.

2

Bright Data

8/10

Pros

  • Advertises a 72M+ residential IP pool
  • Built-in scraping tools and APIs
  • Advanced geo-targeting options
  • Enterprise compliance programs

Cons

  • Complex pricing
  • Bandwidth-based billing can be hard to predict for high-volume agents

Best for: Enterprise AI teams that need a wide product catalog, large advertised pools, and compliance programs.

3

Oxylabs

8/10

Pros

  • Claims a 100M+ residential IP pool
  • Scraper API products handle rotation and rendering
  • Strong technical documentation

Cons

  • Monthly commitments listed from $300+
  • No free trial for most products

Best for: Enterprise-scale LLM data collection with managed scraping APIs and strong documentation.

4

Smartproxy

8/10

Pros

  • Pay-as-you-go residential listed at $7/GB
  • User-friendly dashboard and quick setup
  • Good documentation with code examples

Cons

  • Smaller advertised pool than top-tier providers
  • Limited advanced targeting options

Best for: Mid-market AI teams that want pay-as-you-go residential access with straightforward setup.

5

NetNut

7/10

Pros

  • ISP-sourced static IPs
  • Stable long-lived connections
  • No dependency on peer-to-peer networks

Cons

  • Pricing not publicly listed
  • Sales contact required for most plans

Best for: Long-running agents that prioritize stable, ISP-sourced static connections.

6

SOAX

7/10

Pros

  • Emphasizes ethically sourced residential IPs
  • City-level geo-targeting
  • Real-time proxy health monitoring

Cons

  • Plans listed from $99/month
  • Higher per-GB cost than budget options

Best for: AI data collection where IP sourcing transparency and city-level targeting matter.

7

IPRoyal

7/10

Pros

  • Residential listed from
    .75/GB
  • Non-expiring traffic on some plans
  • Flexible pay-as-you-go model

Cons

  • Smaller advertised pool
  • Inconsistent residential quality reported

Best for: Budget-conscious experiments and intermittent agent jobs.

8

Webshare

7/10

Pros

  • Free tier with 10 datacenter proxies
  • Affordable entry plans
  • Clean management API

Cons

  • Datacenter-only focus limits harder targets
  • Shared IPs can inherit neighbor blocks

Best for: Prototyping agents on a budget before committing to production infrastructure.

9

Zyte

7/10

Pros

  • Smart Proxy Manager with managed rotation
  • Integrates tightly with Scrapy pipelines
  • Listed from $29/month

Cons

  • Not a standalone proxy provider
  • Management layer adds latency versus direct connections

Best for: Scrapy-based data teams that want managed rotation instead of raw proxies.

Quick Comparison

RankProviderRatingBest ForProsCons
1Hex Proxies9/10AI agents and bandwidth-heavy pipelines that benefit from dedicated US ISP IPs with flat per-IP billing.43
2Bright Data8/10Enterprise AI teams that need a wide product catalog, large advertised pools, and compliance programs.42
3Oxylabs8/10Enterprise-scale LLM data collection with managed scraping APIs and strong documentation.32
4Smartproxy8/10Mid-market AI teams that want pay-as-you-go residential access with straightforward setup.32
5NetNut7/10Long-running agents that prioritize stable, ISP-sourced static connections.32
6SOAX7/10AI data collection where IP sourcing transparency and city-level targeting matter.32
7IPRoyal7/10Budget-conscious experiments and intermittent agent jobs.32
8Webshare7/10Prototyping agents on a budget before committing to production infrastructure.32
9Zyte7/10Scrapy-based data teams that want managed rotation instead of raw proxies.32

Our Methodology

Based on publicly available information from each provider’s website as of June 2026. Pool sizes are provider-advertised and not independently verified. AI workloads vary widely — we recommend running your own proof-of-concept with your actual agent framework and target sites before committing.

What AI workloads need from a proxy AI agents and LLM data pipelines tend to hold sessions longer, fan out more parallel requests, and consume more bandwidth than traditional scrapers. That shifts the evaluation toward session stability, predictable billing, and rate-limit headroom rather than raw pool size alone.

How to choose Match the proxy type to the workload: flat-rate ISP proxies suit bandwidth-heavy agents and repeated crawls of known targets, while per-GB residential pools suit geo-distributed collection where location diversity matters more than volume. Whichever you shortlist, test with your actual agent framework — provider-published success rates rarely transfer directly to your targets.

Our Verdict

No single provider fits every AI workload. Per-GB residential pools suit geo-distributed collection, while flat-rate ISP proxies favor bandwidth-heavy agents that hit the same targets repeatedly. Define your stack’s session and bandwidth profile, test a shortlist, and decide on measured results. If you value flat-rate ISP bandwidth and fast setup, Hex Proxies is worth evaluating.

Try Hex Proxies

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