# IP2UP vs Modal

IP2UP records 0 monthly visits with -100% month-over-month growth and Paid, Contact for Pricing pricing. Modal records 1,196,021 monthly visits with +30.2% growth and Freemium, Contact for Pricing pricing.

| Metric | [IP2UP](https://openaitools.app/tool/ip2up-proxy) | [Modal](https://openaitools.app/tool/modal-com) |
| :--- | :--- | :--- |
| Website URL | https://ip2up.com | https://modal.com |
| Categories | AI Web Scraping, AI Data Mining, AI SEO Tools, AI Advertising | AI Developer Tools, AI API, Large Language Models (LLMs), AI Models |
| Pricing Model | Paid, Contact for Pricing | Freemium, Contact for Pricing |
| Monthly Visits | 0 | 1,196,021 |
| MoM Growth Rate | -100% | +30.2% |
| Primary Market | Global | United States |
| Direct Visits | 0 | 845,636 |
| Review Score | 4.2 | 4.8 |
| Saved Count | 0 | 3 |
| Supported Platforms | Website | Website |

## IP2UP

IP2UP is a residential proxy platform built for teams that need to reach the public web from many different locations without getting blocked. Rather than selling generic datacenter IPs, it supplies residential addresses drawn from real consumer connections, which makes requests look like ordinary household traffic. The network claims coverage of 200+ countries and regions with targeting granularity down to country, state, city and ASN.

The product line is split by usage pattern. Dynamic residential proxies bill by bandwidth and rotate IPs, which suits large-scale crawling and price monitoring. Static ISP proxies cost less and give each session a fixed identity, which is useful for logins and long-lived sessions. Unlimited residential proxies bill by time and suit sustained traffic where bandwidth predictability matters more than raw volume.

Integration is developer-focused: ready-made snippets in Python, Node.js, PHP, Go, Java, C++ and cURL, plus developer documentation covering endpoints, authentication and protocols. The company also publishes enterprise-oriented messaging around compliant use, vetted supply and policy-aware controls for public-web data access.

**Pricing & Plans:** Paid, quote-based plus listed reference rates: dynamic residential from $0.45/GB, static residential from $0.16/day, and unlimited residential listed at $10/hour. Enterprise and custom volume plans are handled through sales contact.

- **Three proxy product families:** Rotating dynamic residential billed per GB, static ISP proxies billed per day for stable identities, and unlimited-traffic plans billed per hour for sustained workloads.
- **Fine-grained geo-targeting:** Select exit nodes by country, state, city or ASN so requests appear to originate from the exact market you are researching or verifying.
- **Session and rotation controls:** Tune IP rotation behavior and session stickiness per task, so long-running jobs keep a consistent identity while broad crawls rotate freely.
- **HTTP and SOCKS5 support:** Both protocols are supported across the product line, with ready code samples in Python, Node.js, PHP, Go, Java, C++ and cURL.
- **Coverage across 200+ countries:** A large pool of residential addresses with published per-country supply figures, aimed at multi-region data collection and monitoring.

**Strengths:** Clear product segmentation by workload type (rotating, static, unlimited); Granular targeting including city and ASN level; Straightforward developer onboarding with multi-language code samples; Published per-country IP supply figures for capacity planning

**Limitations:** No self-serve instant pricing for every plan — enterprise deals require contacting sales; Unlimited plans still carry bandwidth, concurrency and duration limits that need reading before purchase; Residential proxy quality varies by location, so benchmarking your own targets first is advisable

[Profile (Markdown)](https://openaitools.app/tool/ip2up-proxy.md)

## Modal

Modal provides cloud infrastructure aimed squarely at AI and data teams. The core idea is that developers write ordinary Python, decorate functions or define container images, and Modal takes care of the underlying compute: scheduling containers, attaching GPUs, autoscaling from zero and back, and exposing endpoints over HTTPS. Infrastructure concerns like networking, storage, and capacity management are abstracted away, so a workload that runs on a laptop can run the same way across a fleet.

The platform is organised around a few primitives. Functions handle serverless compute and can fan out across thousands of GPUs for parallel or batch work. Sandboxes provide isolated environments for coding agents, reinforcement learning rollouts, and other untrusted code, with sub-second start times and support for very high concurrency. Training covers fine-tuning, reinforcement learning, and evaluation on single or multi-node GPU capacity. On the inference side, Modal offers OpenAI-compatible endpoints for open-weight models and lets teams deploy custom stacks and tune endpoints to match their traffic shape.

Underneath, Modal runs its own container runtime and image system designed for large images and fast GPU scheduling, along with a distributed filesystem for fast access to model weights and datasets. Capacity is drawn from a multi-cloud pool spanning many regions, with automatic routing to available hardware and continuous fleet health checks. Billing is usage-based, charged by the second while code runs, with granular cost controls. The company offers a free starting allowance and scalable paid usage, and markets to enterprises with SOC 2 Type II compliance and HIPAA readiness.

**Pricing & Plans:** Modal uses usage-based pricing billed by the second: a free monthly compute allowance gets you started, then you pay for the CPU, memory, and GPU resources your workloads consume. Enterprise plans and startup credits are available, and custom pricing can be discussed with sales.

- **Serverless Python functions:** Write plain Python, attach GPUs or containers, and deploy HTTPS endpoints that autoscale with traffic and scale to zero when idle.
- **Sandboxes for agents:** Launch isolated, secure environments for coding agents, RL rollouts, and untrusted code, with sub-second starts and support for over a million concurrent sandboxes.
- **Training and fine-tuning on demand:** Run fine-tunes, LoRA, full training, and reinforcement learning on elastic single or multi-node GPU capacity with no quota requests.
- **Model inference and endpoints:** Serve LLMs and image, video, or audio models through OpenAI-compatible endpoints, or bring your own inference stack and let Modal handle the infrastructure.
- **Fast storage and multi-cloud capacity:** A distributed filesystem loads large images and model weights at full bandwidth, while a pool spanning 20+ clouds routes workloads to the right hardware and region.

**Strengths:** Python-native developer experience with almost no infrastructure boilerplate; Scales from zero to thousands of GPUs with per-second, usage-based billing; Sandboxes are well suited to agentic and untrusted-code workloads; Multi-cloud capacity spans many regions with out-of-the-box observability and enterprise compliance

**Limitations:** Billed by real usage, so heavy GPU workloads can get expensive quickly without cost controls; Some advanced inference and enterprise features require working with the team rather than self-serve signup; The serverless model can feel less familiar to teams used to managing their own VMs or Kubernetes clusters

[Profile (Markdown)](https://openaitools.app/tool/modal-com.md)

## Frequently Asked Questions

### How do IP2UP and Modal compare in monthly traffic?

IP2UP has 0 monthly visits, while Modal has 1,196,021. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

IP2UP has a month-over-month growth rate of -100%; Modal has +30.2%.

### How does pricing compare?

IP2UP: Paid, Contact for Pricing. Paid, quote-based plus listed reference rates: dynamic residential from $0.45/GB, static residential from $0.16/day, and unlimited residential listed at $10/hour. Enterprise and custom volume plans are handled through sales contact. Modal: Freemium, Contact for Pricing. Modal uses usage-based pricing billed by the second: a free monthly compute allowance gets you started, then you pay for the CPU, memory, and GPU resources your workloads consume. Enterprise plans and startup credits are available, and custom pricing can be discussed with sales.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Extremely fast serverless execution optimized specifically for generative media models rather than general Python code. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 2 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | Provides flexible GPU infrastructure and serverless endpoints, though less focused on pure Python function decorators. | [.md](https://openaitools.app/tool/runpod.md) |
| 3 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Focuses heavily on managed open-source model inference APIs rather than arbitrary custom container execution. | [.md](https://openaitools.app/tool/together-ai.md) |
| 4 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Rent cloud GPUs by the second from a global marketplace | [.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 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | Delivers robust enterprise GPU clusters and managed inference, requiring more infrastructure setup than Modal's serverless approach. | [.md](https://openaitools.app/tool/nebius.md) |
| 7 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Easier model packaging via Cog, but offers less arbitrary serverless Python container execution than Modal. | [.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 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Low-cost serverless inference APIs for 200+ open models | [.md](https://openaitools.app/tool/deep-infra.md) |
| 10 | [Lightning AI](https://openaitools.app/tool/lightning-ai) | 272,562 | -12.3% | Freemium, Paid, Contact for Pricing | Provides integrated development studios and training workflows, but with less granular serverless function orchestration. | [.md](https://openaitools.app/tool/lightning-ai.md) |

---
Source: https://openaitools.app/compare/ip2up-proxy-vs-modal-com

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