# Modal vs PROXY.CC

Modal records 1,196,021 monthly visits with +30.2% month-over-month growth and Freemium, Contact for Pricing pricing. PROXY.CC records 17,415 monthly visits with -40.2% growth and Free pricing.

| Metric | [Modal](https://openaitools.app/tool/modal-com) | [PROXY.CC](https://openaitools.app/tool/proxycc) |
| :--- | :--- | :--- |
| Website URL | https://modal.com | https://proxy.cc/?keyword=z9mk0exv |
| Categories | AI Developer Tools, AI API, Large Language Models (LLMs), AI Models | AI Web Scraping, AI SEO Tools, AI Advertising |
| Pricing Model | Freemium, Contact for Pricing | Free |
| Monthly Visits | 1,196,021 | 17,415 |
| MoM Growth Rate | +30.2% | -40.2% |
| Primary Market | United States | Brazil |
| Direct Visits | 845,636 | 9,648 |
| Review Score | 4.8 | 4.2 |
| Saved Count | 3 | 0 |
| Supported Platforms | Website | Website |

## 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)

## PROXY.CC

PROXY.CC sells access to a large IP pool marketed at 90M+ addresses spanning 190+ cities worldwide, with country, state and city-level targeting available. The lineup covers several distinct proxy types so teams can match the tool to the job: rotating residential proxies for scraping and crawling, static residential proxies with fixed IPs and unlimited traffic, unlimited residential plans, static datacenter proxies with high accuracy claims, and long-acting ISP proxies designed for longer uninterrupted sessions.

Operationally the platform emphasises flexible configuration. Users authenticate via username and password or IP whitelisting, can create sub-users, choose proxies from many countries, fine-tune sessions by ISP and protocol, and control rotation by time or request with auto-replacement. There are no limits on concurrent sessions or invocation frequency, and documentation covers API parameter configurations plus code samples for Python, Node.js, PHP, Go, Java, C#, Shell and Ruby.

Common use cases the provider highlights include market research, brand protection, ad verification, web scraping and crawling, SEO monitoring and social media marketing, with country and city-level geo-targeting and a stated 99.5% success rate. A proxy checker and free proxy list are offered as free tools, and the site supports many interface languages plus partner and affiliate programs.

**Pricing & Plans:** PROXY.CC prices each proxy type separately: rotating residential proxies from a per-GB rate, static residential and static datacenter proxies from a per-IP-per-day rate, unlimited residential plans from a per-day rate, and long-acting ISP proxies from a per-GB rate. Current rates and plan details are listed on the site's pricing page.

- **90M+ IP pool across 190+ locations:** A large residential and datacenter network with country, state, city and ASN-level targeting options.
- **Multiple proxy product lines:** Rotating residential, static residential, unlimited residential, static datacenter and long-acting ISP proxies to match different workload types.
- **Flexible authentication and control:** User/pass or IP whitelist authentication, sub-user creation, ISP and protocol filtering, plus rotation by time or request with auto-replace.
- **Developer-friendly API:** Documented API parameters with code samples for Python, Node.js, PHP, Go, Java, C#, Shell and Ruby.
- **Free utility tools:** A proxy checker and free proxy list are available alongside the paid network for quick testing.

**Strengths:** Very large IP pool with granular country, city and ASN targeting; Several proxy types so teams can match rotating, sticky or unlimited needs; No limits on concurrent sessions or invocation frequency; Documented API with samples in many common programming languages

**Limitations:** Proxy pricing is split across many product lines, so cost needs careful comparison; The site is a marketing-heavy service page with limited independent performance benchmarks; Effectiveness ultimately depends on your target sites' anti-bot measures

[Profile (Markdown)](https://openaitools.app/tool/proxycc.md)

## Frequently Asked Questions

### How do Modal and PROXY.CC compare in monthly traffic?

Modal has 1,196,021 monthly visits, while PROXY.CC has 17,415. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Modal has a month-over-month growth rate of +30.2%; PROXY.CC has -40.2%.

### How does pricing compare?

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. PROXY.CC: Free. PROXY.CC prices each proxy type separately: rotating residential proxies from a per-GB rate, static residential and static datacenter proxies from a per-IP-per-day rate, unlimited residential plans from a per-day rate, and long-acting ISP proxies from a per-GB rate. Current rates and plan details are listed on the site's pricing page.

## 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/modal-com-vs-proxycc

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