# IPPeak vs RunPod

IPPeak records 25,571 monthly visits with +20.9% month-over-month growth and Paid pricing. RunPod records 2,881,043 monthly visits with +5.9% growth and Paid pricing.

| Metric | [IPPeak](https://openaitools.app/tool/ippeak) | [RunPod](https://openaitools.app/tool/runpod) |
| :--- | :--- | :--- |
| Website URL | https://www.ippeak.com | https://runpod.io |
| Categories | Other | AI Developer Tools, AI Models, Large Language Models (LLMs), AI API |
| Pricing Model | Paid | Paid |
| Monthly Visits | 25,571 | 2,881,043 |
| MoM Growth Rate | +20.9% | +5.9% |
| Primary Market | China | United States |
| Direct Visits | 14,084 | 1,634,834 |
| Review Score | 4 | 4.7 |
| Saved Count | 0 | 4 |
| Supported Platforms | Website | Website |

## IPPeak

IPPeak supplies the network layer that data-heavy teams need: rotating residential IPs sourced from real residential connections, static ISP proxies with dedicated addresses, and an unlimited residential option that removes traffic metering entirely. The pool is advertised at more than 80 million IPs across 195+ countries, with geo and ASN targeting, unlimited concurrent sessions, a stated 99.95% connection success rate and sub-half-second average response times. Both HTTP and SOCKS5 are supported.

Pricing is structured around workload shape rather than a single flat fee. Smaller or budget-sensitive projects go on Core Residential at roughly $0.49 per GB of traffic. Teams that need consistent, high-quality exit IPs can move to the Premium Residential tier from about $0.60 per GB with geo/ASN targeting and 80M+ curated pool access. Static ISP proxies bill per IP per day from around $0.12 and include unlimited bandwidth in 30+ countries, while the Unlimited Residential plan from roughly $8 per hour lifts traffic and IP caps for high-volume operations. Pricing is quoted per unit and volume discounts typically apply at scale.

Setup is intentionally ordinary: create a subscription, configure an endpoint in the dashboard, receive proxy credentials (IP, port, authentication), then drop them into your scraping stack. Documentation spans C/C++, Go, Node.js, PHP, Java and Python. The company markets a no-logs policy, and the site frames its use cases around compliant access to publicly available data. Buyers should evaluate proxy vendors on pool diversity, success rates and legal compliance for their specific jurisdiction.

**Pricing & Plans:** Product-based pricing rather than a single subscription: Core Residential from about $0.49/GB, Premium Residential from about $0.60/GB with geo/ASN targeting, ISP proxies from about $0.12 per IP per day with unlimited bandwidth, and Unlimited Residential Proxies from about $8 per hour. Volume discounts apply; there is no free tier advertised.

- **80M+ residential IP pool:** Rotating residential addresses sourced from real residential networks across more than 195 countries, with geo and ASN targeting options.
- **Static ISP proxies:** Fully dedicated static residential IPs with unlimited bandwidth available in 30+ countries, billed per IP per day for long-term stable sessions.
- **Unlimited residential plan:** An hourly plan with no traffic or IP limits, aimed at heavy scraping workloads that would be expensive under per-GB billing.
- **Performance claims:** Unlimited concurrent sessions, a stated 99.95% connection success rate and average response times under 0.5 seconds.
- **Developer integrations:** HTTP and SOCKS5 endpoints with code samples for Python, Node.js, Go, Java, PHP and C/C++, plus a dashboard for endpoint configuration.

**Strengths:** Multiple proxy types in one provider, so a project can mix per-GB, per-IP and hourly billing; Very large advertised IP pool with 195+ country coverage and ASN targeting; Fast documented integration with samples for six common languages; Static ISP option includes unlimited bandwidth and dedicated addresses

**Limitations:** No free tier or trial minutes advertised, so evaluation requires a purchase; Per-GB pricing can become costly for very large continuous scraping jobs; Performance figures such as the 99.95% success rate come from the vendor and should be validated on your own targets

[Profile (Markdown)](https://openaitools.app/tool/ippeak.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 IPPeak and RunPod compare in monthly traffic?

IPPeak has 25,571 monthly visits, while RunPod has 2,881,043. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

IPPeak has a month-over-month growth rate of +20.9%; RunPod has +5.9%.

### How does pricing compare?

IPPeak: Paid. Product-based pricing rather than a single subscription: Core Residential from about $0.49/GB, Premium Residential from about $0.60/GB with geo/ASN targeting, ISP proxies from about $0.12 per IP per day with unlimited bandwidth, and Unlimited Residential Proxies from about $8 per hour. Volume discounts apply; there is no free tier advertised. 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 | [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) |
| 6 | [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) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 10 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Delivers exceptionally low-cost serverless model inference, but does not provide raw GPU container rentals for custom training workloads. | [.md](https://openaitools.app/tool/deep-infra.md) |

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Source: https://openaitools.app/compare/ippeak-vs-runpod

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)