# Hugging Face vs Quick Intel

Hugging Face records 31,232,542 monthly visits with +0.1% month-over-month growth and Freemium, Paid pricing. Quick Intel records 7,800 monthly visits with +35.9% growth and Free pricing.

| Metric | [Hugging Face](https://openaitools.app/tool/hugging-face) | [Quick Intel](https://openaitools.app/tool/quickintel-io) |
| :--- | :--- | :--- |
| Website URL | https://huggingface.co | https://quickintel.io |
| Categories | Open Source AI Models, AI Models, AI Developer Tools, Large Language Models (LLMs) | AI Crypto, Web3, AI API, AI Detector |
| Pricing Model | Freemium, Paid | Free |
| Monthly Visits | 31,232,542 | 7,800 |
| MoM Growth Rate | +0.1% | +35.9% |
| Primary Market | United States | Indonesia |
| Direct Visits | 13,401,480 | 5,037 |
| Review Score | 4.8 | 4.2 |
| Saved Count | 11 | 5 |
| Supported Platforms | Website | Website |

## Hugging Face

Hugging Face began as a chatbot startup and grew into what is now widely described as the home of machine learning. The core of the product is the Hub: a public, searchable registry of model weights, datasets, and interactive Spaces demos. On a typical visit you will see millions of models ranging from large language and vision models published by major labs to small fine-tunes shared by individual developers, each with model cards, libraries, and one-click inference options.

Around that registry Hugging Face has built a full working stack. Its open-source libraries — Transformers, Diffusers, Datasets, Tokenizers, Accelerate, PEFT, TRL, and smolagents — power a large share of modern training and inference pipelines, and the Hub integrates directly with them. Teams can also move beyond public hosting: Inference Providers give a single API across tens of thousands of hosted models, Inference Endpoints deploy dedicated GPUs, and Enterprise plans add SSO, audit logs, private datasets, and priority support.

The platform is free to browse, upload, and collaborate on for public content, with paid tiers for individuals, teams, and enterprises that need private storage, higher limits, and compute. Because the community continuously publishes papers, blog posts, daily papers digests, and leaderboards in the same place, Hugging Face doubles as a discovery layer for what is happening in AI right now.

**Pricing & Plans:** Free for public hosting, browsing, and community use. Paid options include a PRO individual tier, Team & Enterprise plans starting around $20 per user per month, Inference Providers usage-based API pricing, and dedicated Inference Endpoints from roughly $0.60 per GPU hour. Exact rates change, so check the official pricing page.

- **Model and dataset Hub:** Search, download, and publish across millions of models and hundreds of thousands of datasets, complete with model cards, versioning, and citations.
- **Spaces demo hosting:** Deploy Gradio, Streamlit, or static apps directly from a repository to show off a model, run comparisons, or share a tool with a public link.
- **Open-source library stack:** Transformers, Diffusers, Datasets, Tokenizers, Accelerate, PEFT, TRL, and smolagents give you end-to-end tooling for training, fine-tuning, and inference.
- **Unified inference access:** Inference Providers route a single API to tens of thousands of models from multiple vendors, while Inference Endpoints spin up dedicated GPU hardware on demand.
- **Enterprise governance:** Team and Enterprise plans add SSO, audit logs, resource groups, private repositories, region choice, and dedicated support for regulated organizations.

**Strengths:** Unmatched catalog of open models, datasets, and ready-to-run demos; First-party libraries that most teams in the ecosystem already use; Free public hosting with a clear upgrade path to paid compute and enterprise controls; Strong community signals such as downloads, likes, leaderboards, and daily papers

**Limitations:** The catalog is so large that quality varies widely and discovery takes effort; Paid compute and enterprise tiers scale in cost quickly for heavy workloads; Some popular features depend on community-maintained repos that may fall out of date

[Profile (Markdown)](https://openaitools.app/tool/hugging-face.md)

## Quick Intel

Quick Intel has evolved into a token security infrastructure layer for Web3 products. Instead of being an end-user scanner alone, it now sells risk intelligence through APIs that builders embed directly into wallets, trading interfaces, DeFi dashboards, and Telegram or Discord bots. The site emphasizes getting mature token risk data without rebuilding scanner infrastructure or negotiating enterprise contracts.

The platform covers a broad set of security signals: token identity and ownership, honeypot detection, buy and sell taxes, price impact, liquidity depth, holder distribution, and contract authority functions such as mint, blacklist, fee modification, max wallet, and pause. It also analyzes deployer history, which helps surface tokens created by wallets with a track record of scams. These checks are returned in normalized responses so results are consistent across chains.

Scale is a central part of the pitch — 60+ chains, over 75 million unique tokens scanned, and more than 15 million API calls weekly, with integrations reaching DEXTools, DexScreener, GeckoTerminal, wallets, bots, and security partners. Quick Intel also ships consumer-facing surfaces: iOS and Android apps, a web app, Discord and Telegram bots, and a MetaMask Snap, so the same intelligence is available at the point of decision and through an API. A free tier lets teams test the endpoints before committing to a paid plan.

**Pricing & Plans:** Quick Intel offers a free tier to try the APIs, with paid API plans that scale by traffic and coverage. Consumer apps and bots are also available. Check the API pricing page for the current tiers.

- **Token identity and qHash matching:** Single-call endpoints return token identity, ownership, and a qHash match so you can identify and compare tokens quickly.
- **Real-time risk signals:** Flags honeypots, buy and sell taxes, transfer restrictions, and other danger signals in real time as trades happen.
- **Contract authority checks:** Detects mint, blacklist, fee-modification, max-wallet, pause, and other scam-capable functions in contract code.
- **Liquidity and holder intelligence:** Track liquidity depth, holder distribution, and deployer history to judge how sound or concentrated a token is.
- **Developer-first API:** Endpoint docs and integrations let you embed security signals in wallets, trading tools, scanners, and bots via REST API.

**Strengths:** Wide chain coverage with normalized API responses; Strong coverage of honeypot, tax, and contract authority checks; Multiple access points: apps, bots, a MetaMask Snap, and APIs; Free tier available for testing and smaller projects

**Limitations:** Focused on developers and API integration, so non-technical traders get less value; Token risk scores are signals, not guarantees — false positives and false negatives happen; Full coverage depends on plan tier and rate limits; Crypto security data can quickly go stale as contracts change

[Profile (Markdown)](https://openaitools.app/tool/quickintel-io.md)

## Frequently Asked Questions

### How do Hugging Face and Quick Intel compare in monthly traffic?

Hugging Face has 31,232,542 monthly visits, while Quick Intel has 7,800. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Hugging Face has a month-over-month growth rate of +0.1%; Quick Intel has +35.9%.

### How does pricing compare?

Hugging Face: Freemium, Paid. Free for public hosting, browsing, and community use. Paid options include a PRO individual tier, Team & Enterprise plans starting around $20 per user per month, Inference Providers usage-based API pricing, and dedicated Inference Endpoints from roughly $0.60 per GPU hour. Exact rates change, so check the official pricing page. Quick Intel: Free. Quick Intel offers a free tier to try the APIs, with paid API plans that scale by traffic and coverage. Consumer apps and bots are also available. Check the API pricing page for the current tiers.

## 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 | A unified API gateway routing requests across hundreds of language models, but lacking dataset hosting. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 2 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Enables running and managing open-source LLMs locally on your hardware instead of relying on cloud hosting. | [.md](https://openaitools.app/tool/ollama.md) |
| 3 | [Civitai](https://openaitools.app/tool/civitai) | 6,963,136 | +12.8% | Freemium | Focuses strictly on community-driven discovery and sharing of generative image and video models rather than text LLMs. | [.md](https://openaitools.app/tool/civitai.md) |
| 4 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | One API for 1,500+ production-ready generative media models | [.md](https://openaitools.app/tool/fal-ai.md) |
| 5 | [ModelScope](https://openaitools.app/tool/modelscope-community) | 3,085,423 | +5.1% | Free | An alternative open-source model repository and community hub, featuring extensive regional models and online interactive demos. | [.md](https://openaitools.app/tool/modelscope-community.md) |
| 6 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Provides robust serverless inference and fine-tuning APIs for open-source models, replacing Hugging Face's hosted endpoints. | [.md](https://openaitools.app/tool/together-ai.md) |
| 7 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Offers cloud APIs for running and fine-tuning machine learning models with simpler pricing than custom infrastructure. | [.md](https://openaitools.app/tool/replicate-ai.md) |
| 8 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Open-source, memory-efficient fine-tuning and local model running | [.md](https://openaitools.app/tool/unsloth-ai.md) |
| 9 | [Fireworks](https://openaitools.app/tool/fireworks-ai) | 659,687 | +6% | Contact for Pricing | Delivers ultra-fast serverless inference for open-weight models, prioritizing production throughput over community dataset sharing. | [.md](https://openaitools.app/tool/fireworks-ai.md) |
| 10 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Provides low-cost serverless inference and GPU rentals for open models, though without community spaces and datasets. | [.md](https://openaitools.app/tool/deep-infra.md) |

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Source: https://openaitools.app/compare/hugging-face-vs-quickintel-io

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