# AProxy vs RunPod AProxy records 36,540 monthly visits with -41.4% month-over-month growth and Free Trial, Paid pricing. RunPod records 2,881,043 monthly visits with +5.9% growth and Paid pricing. | Metric | [AProxy](https://openaitools.app/tool/aproxy) | [RunPod](https://openaitools.app/tool/runpod) | | :--- | :--- | :--- | | Website URL | https://aproxy.com/?keyword=unw8l6dq | https://runpod.io | | Categories | AI Web Scraping, AI For Data Analytics, AI Developer Tools, AI API | AI Developer Tools, AI Models, Large Language Models (LLMs), AI API | | Pricing Model | Free Trial, Paid | Paid | | Monthly Visits | 36,540 | 2,881,043 | | MoM Growth Rate | -41.4% | +5.9% | | Primary Market | Brazil | United States | | Direct Visits | 15,256 | 1,634,834 | | Review Score | 4.1 | 4.7 | | Saved Count | 0 | 4 | | Supported Platforms | Website | Website | ## AProxy AProxy sells access to a global proxy network and the tooling needed to use that network productively. The core offering is a pool of more than 70 million residential IPs spanning 195+ countries, with sub-second connection times and 99.9% availability claims. Around that pool the company layers several IP classes: rotating residential proxies for sensitive scraping targets, longer-session ISP proxies that blend datacenter speed with residential trust, static residential addresses that never rotate, and static datacenter IPs for high-throughput jobs that do not need residential reputation. Beyond raw IPs, AProxy ships scraping-oriented APIs. The Web Scraper API exposes dedicated endpoints for 100+ domains, the Universal Scraper API simulates real user behavior to get past anti-bot defenses, the SERP API returns structured search results from Google and Bing in real time, and the Video Data API is designed for large-scale video metadata collection with cloud storage included. Documented target platforms include Google, Bing, YouTube, DuckDuckGo, Instagram, Facebook, Amazon, and Walmart. The platform is positioned squarely at AI and data teams: the marketing landing copy talks about empowering LLMs and automation workflows with reliable web data, and the use-case list covers crawl proxies, market research, SEO rank tracking, price monitoring, ad verification, brand protection, and multi-account social media management. Management tools include a usage dashboard, flexible API endpoints for configuration and real-time IP rotation, 1000+ city-level geo-targeting, a proxy checker, and third-party integrations. Support is available via email with a 24-hour response target, and the company states ISO/IEC 27001:2017 certification for its processes. **Pricing & Plans:** Usage-based pricing with a free trial. Public rate cards start around $0.50/GB for rotating residential traffic, roughly $0.27/GB for long-acting ISP proxies, and per-IP pricing for static residential and static datacenter addresses. Unlimited residential plans are quoted from about $67.87/day, and scraping APIs are metered per 1,000 results. Custom enterprise and affiliate programs are also offered. - **70M+ IP pool across 195+ countries:** Rotating residential, ISP, static residential, and static datacenter IPs with city-level targeting in 1000+ locations and sub-second connection times. - **Purpose-built scraping APIs:** Web Scraper API with 100+ dedicated domain endpoints, a Universal Scraper API that mimics real users to defeat anti-bot systems, a real-time SERP API, and a Video Data API with integrated cloud storage. - **Flexible rotation and session control:** API endpoints let you configure proxy settings and rotate IPs in real time, while ISP proxies support sessions of up to 12 hours for jobs that need a stable identity. - **Management dashboard and tooling:** Usage tracking, subaccounts and whitelists, a country code lookup, and a proxy checker for validating connectivity before you deploy. - **Compliance and security posture:** Compliant-source IP sourcing and ISO/IEC 27001:2017 certification, with documented support channels for enterprise procurement. **Strengths:** Broad IP type coverage (rotating, ISP, static residential, datacenter) from a single vendor; Ready-made scraping and SERP APIs remove the need to build anti-bot handling yourself; Large, well-documented geo-targeting footprint with city-level selection; Transparent public rate cards and a free trial for testing before committing **Limitations:** Pricing is metered by bandwidth or result count, so heavy workloads scale costs quickly; Unlimited residential plans are priced per day, which is expensive for occasional users; No fully free tier beyond trial credits, which limits casual evaluation [Profile (Markdown)](https://openaitools.app/tool/aproxy.md) ## RunPod The platform is organised around three products. Pods give you a persistent GPU instance with your own container, framework and code, available as guaranteed Reserved capacity or lower-priced interruptible instances. Serverless turns a container into an autoscaling HTTP or queue-driven endpoint that spins workers up and down with demand. Clusters connect many GPUs across nodes for distributed training and large-scale inference, with shared storage attached. Around these sit a Model Hub of deployable templates and public endpoints for hosted image, audio and text models. Operationally, RunPod leans on fast provisioning and scale-to-zero economics. A GPU pod can be running in under a minute, workloads spread across 31 regions, and Serverless endpoints expand from zero to hundreds of concurrent workers automatically without hand-written orchestration. Storage is persistent and priced in tiers, which suits pipelines that keep checkpoints and datasets around between runs. RunPod is a popular choice for developers, research teams and AI startups because it removes the need to negotiate long-term contracts with hyperscale clouds while still offering enterprise features such as SOC 2 Type II compliance, 99.9% uptime targets and failover handling. It is best suited to teams who are comfortable working in containers and want direct control over GPU cost and configuration. **Pricing & Plans:** Paid, pay-as-you-go. GPU Pods are billed per second or per hour by card type, Serverless endpoints bill for active compute only with zero idle cost, and Clusters charge per GPU per hour. Storage starts at around $0.05/GB per month. A free tier and enterprise reserved-capacity contracts are also available. - **On-demand GPU Pods:** Rent GPU instances with on-demand, interruptible or reserved capacity across more than 30 GPU SKUs, from RTX 4090s up to B200 and B300 class accelerators, deployed in 31 global regions. - **Autoscaling Serverless endpoints:** Deploy any container as an API endpoint that scales from zero to thousands of workers on demand and bills only for the compute you actually use. - **Multi-node Clusters:** Launch multi-node GPU clusters for distributed training and large inference jobs, with shared storage attachable and no long-term commitment required. - **Model Hub and public endpoints:** Deploy popular open-source models from a curated hub, or use public endpoints for image, audio and text models without managing infrastructure. - **Persistent storage:** Persistent network storage with standard and high-performance tiers, container and volume disks, and no egress fees for full AI pipelines. **Strengths:** Extremely broad GPU catalogue spanning consumer and datacentre cards; Per-second billing and scale-to-zero serverless endpoints keep idle costs near zero; Fast environment provisioning from templates or your own containers; Global region coverage with persistent storage and no egress fees **Limitations:** GPU availability for high-end cards can vary by region and time of day; Serverless cold starts and autoscaling behaviour require some tuning to get right; Costs can climb quickly if workloads are left running on idle Pods; Learning curve for container and handler configuration is steeper than fully managed model APIs [Profile (Markdown)](https://openaitools.app/tool/runpod.md) ## Frequently Asked Questions ### How do AProxy and RunPod compare in monthly traffic? AProxy has 36,540 monthly visits, while RunPod has 2,881,043. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? AProxy has a month-over-month growth rate of -41.4%; RunPod has +5.9%. ### How does pricing compare? AProxy: Free Trial, Paid. Usage-based pricing with a free trial. Public rate cards start around $0.50/GB for rotating residential traffic, roughly $0.27/GB for long-acting ISP proxies, and per-IP pricing for static residential and static datacenter addresses. Unlimited residential plans are quoted from about $67.87/day, and scraping APIs are metered per 1,000 results. Custom enterprise and affiliate programs are also offered. RunPod: Paid. Paid, pay-as-you-go. GPU Pods are billed per second or per hour by card type, Serverless endpoints bill for active compute only with zero idle cost, and Clusters charge per GPU per hour. Storage starts at around $0.05/GB per month. A free tier and enterprise reserved-capacity contracts are also available. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Provides a unified API gateway across hundreds of models, but entirely abstracts away underlying GPU infrastructure management. | [.md](https://openaitools.app/tool/openrouter-ai.md) | | 2 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Specializes in lightning-fast serverless execution for generative media models, but lacks general-purpose GPU pod rental options. | [.md](https://openaitools.app/tool/fal-ai.md) | | 3 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Delivers managed serverless model inference and GPU clusters, trading raw bare-metal pod customization for streamlined API access. | [.md](https://openaitools.app/tool/together-ai.md) | | 4 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Offers a peer-to-peer GPU rental marketplace with often lower prices, but with more variable hardware reliability than RunPod. | [.md](https://openaitools.app/tool/vast-ai.md) | | 5 | [Browser Use](https://openaitools.app/tool/browser-use) | 1,206,376 | +41.1% | Freemium, Paid, Contact for Pricing | Browser agents and stealth cloud browsers for real web tasks | [.md](https://openaitools.app/tool/browser-use.md) | | 6 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Provides serverless Python execution and instant container scaling, but lacks direct persistent SSH pod control like RunPod. | [.md](https://openaitools.app/tool/modal-com.md) | | 7 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | Offers high-performance enterprise NVIDIA GPU clusters, but focuses more on dedicated bare-metal infrastructure than flexible spot pods. | [.md](https://openaitools.app/tool/nebius.md) | | 8 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Offers a polished API and cloud platform for running open models, but provides less direct infrastructure-level control than RunPod. | [.md](https://openaitools.app/tool/replicate-ai.md) | | 9 | [Bright Data](https://openaitools.app/tool/bright-data) | 802,752 | -5.9% | Free Trial, Paid | Web data infrastructure for scraping, proxies, and AI-ready datasets | [.md](https://openaitools.app/tool/bright-data.md) | | 10 | [Salad](https://openaitools.app/tool/salad-gpu-cloud) | 713,519 | +10.4% | Free Trial, Paid, Contact for Pricing | Utilizes distributed consumer hardware to drastically lower inference costs, but cannot match enterprise GPU availability or SLA guarantees. | [.md](https://openaitools.app/tool/salad-gpu-cloud.md) | --- Source: https://openaitools.app/compare/aproxy-vs-runpod More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)