# Dify vs GPUPerHour

Dify records 819,691 monthly visits with -15% month-over-month growth and Freemium pricing. GPUPerHour records 28,718 monthly visits with +25.3% growth and Free pricing.

| Metric | [Dify](https://openaitools.app/tool/dify-ai) | [GPUPerHour](https://openaitools.app/tool/gpuperhour) |
| :--- | :--- | :--- |
| Website URL | https://dify.ai | https://gpuperhour.com |
| Categories | AI App Builder, AI Agent, AI Workflow, AI API | AI Developer Tools, AI Tools Directory |
| Pricing Model | Freemium | Free |
| Monthly Visits | 819,691 | 28,718 |
| MoM Growth Rate | -15% | +25.3% |
| Primary Market | China | United States |
| Direct Visits | 470,604 | 11,398 |
| Review Score | 4.8 | 4.4 |
| Saved Count | 22 | 4 |
| Supported Platforms | Website | Website |

## Dify

Dify pairs a visual canvas with code-level control so both technical and non-technical teams can assemble AI applications and agents. Workflow Studio turns prompt logic into an inspectable execution graph of building blocks: retrieval, branching, tool calls, human-in-the-loop steps, and model calls. Agent builder lets you create agents by chatting or by configuring them directly, then run them as a standalone app, embed them into a website, or reuse them as a node inside a larger workflow.

A major part of the platform is context engineering. The Knowledge Pipeline lets you define repeatable ingestion flows for files, websites, online documents, and cloud drives, handling extraction, cleaning, chunking, indexing, and retrieval testing before a knowledge base is attached to agents or workflows. The Marketplace supplies model providers, tools, data sources, and MCP integrations that teams can install once and then reuse across many apps as approved plugins.

Dify ships in three deployment shapes: Dify Cloud (fully managed SaaS with workspace, logs, and scaling handled for you), Dify Enterprise (self-hosted or VPC deployment with SSO/SAML, RBAC, audit logs, Helm charts for Kubernetes, and enterprise support), and the open-source Community Edition, a source-available single-command Docker deployment with a large GitHub community. Published apps can be delivered as hosted web apps, API endpoints, embeds, or MCP-compatible tools, with logs, feedback, annotations, latency, and usage analytics to keep improving them after launch.

**Pricing & Plans:** Freemium model with a free cloud sandbox and free trial credits, paid Cloud plans that scale with team size, storage, logs, and usage, and a free open-source Community Edition. Dify Enterprise is quoted per deployment via sales.

- **Workflow Studio:** A visual canvas where retrieval, branching, tool calls, human review, and model steps form a visible, testable execution path you can debug and hand off.
- **Agent Builder:** Create agents through chat or manual configuration, give them skills, tools, and knowledge, then ship them as apps, embeds, or reusable nodes inside workflows.
- **Knowledge Pipeline:** Build repeatable ingestion pipelines for documents, sites, and drives, with extraction, cleaning, chunking, indexing, and retrieval testing before you go live.
- **Plugin Marketplace and MCP:** Install model providers, tools, data sources, and MCP integrations once and reuse approved plugins across every app in the workspace.
- **Flexible Deployment and Observability:** Run on managed Cloud, in your VPC, or self-hosted with Docker, and monitor published apps through logs, annotations, feedback, latency, and usage data.

**Strengths:** Combines a visual builder with code-level extensibility in one product; Three deployment options, including a free self-hosted Community Edition; Strong retrieval and knowledge pipeline tooling for RAG applications; Large plugin marketplace plus MCP support reduces integration work

**Limitations:** Self-hosted deployments require real infrastructure and maintenance effort; Complex multi-step workflows take time to learn and tune; Advanced enterprise governance features sit behind a sales-quoted plan

[Profile (Markdown)](https://openaitools.app/tool/dify-ai.md)

## GPUPerHour

GPUPerHour solves a narrow but expensive problem: cloud GPU pricing is scattered across dozens of provider dashboards, in different units and with different availability. The site periodically scrapes the public pricing and inventory endpoints of 31 cloud GPU providers, normalises each listing to a price per GPU per hour (dividing a multi-GPU instance price by its GPU count) and tags it with its pricing type and security tier. The current-price summary deliberately uses only secure on-demand offers observed within roughly 15 minutes of the last refresh, excluding spot, reserved and peer-to-peer marketplace listings because those prices are not directly comparable.

The result is a single live table covering H100 SXM5 and PCIe, H200, B200, B300, A100 80GB and 40GB, L40S, RTX PRO 6000, RTX 5090, RTX 4090 and RTX A6000, alongside the provider, a 30-day historical catalog average and the number of providers with stock. A daily price index with CSV downloads lets you track how pricing moves over time, while buying guides and hardware explainers cover practical topics such as comparing like-for-like GPUs, choosing by VRAM for a workload, accounting for storage and egress, and renting by the hour. The site also points to a companion console, DeployGPU, for provisioning on supported providers from one place.

The key caveat is stated openly on the page: offer counts describe configurations, not the number of physical GPUs bookable, and availability can change before you complete a booking. Prices are per GPU-hour but providers bill for the whole instance, and storage, network transfer and commitment terms affect the final bill. GPUPerHour is a research and comparison layer, not a hosting provider itself.

**Pricing & Plans:** Free to use as a price-comparison and research resource; GPUPerHour does not sell GPU capacity itself. The prices shown are third-party provider rates for secure on-demand instances, per GPU-hour, and a companion service (DeployGPU) offers deployment on supported providers.

- **31-provider live price table:** Every tracked offer is normalised to a price per GPU-hour and shown with its provider, pricing type and security tier.
- **Cheapest-offer summary:** A market snapshot highlights the lowest current secure on-demand price for each popular GPU model, from H100 and H200 to RTX 4090.
- **Daily price index and CSV:** Historical catalog averages and downloadable daily data let you see how pricing for a given GPU has moved over the last 30 days.
- **Buying guides and explainers:** Practical articles cover comparing like-for-like GPUs, choosing by VRAM, estimating the full bill with storage and egress, and renting by the hour.
- **DeployGPU console:** A linked console lets you deploy on supported providers from a single place once you have picked an offer.

**Strengths:** Aggregates 31 providers into comparable per-GPU-hour prices; Clearly states its methodology and excludes non-comparable spot and P2P listings; Free to use, with daily historical data and CSV downloads; Buying guides cover the full bill, not just the headline rate

**Limitations:** Only covers providers whose pricing and inventory endpoints are publicly scrapable; The current-price view deliberately excludes spot and reserved capacity, which are often cheaper; It is a comparison resource, so you still create accounts and provision instances with the provider itself

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

## Frequently Asked Questions

### How do Dify and GPUPerHour compare in monthly traffic?

Dify has 819,691 monthly visits, while GPUPerHour has 28,718. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Dify has a month-over-month growth rate of -15%; GPUPerHour has +25.3%.

### How does pricing compare?

Dify: Freemium. Freemium model with a free cloud sandbox and free trial credits, paid Cloud plans that scale with team size, storage, logs, and usage, and a free open-source Community Edition. Dify Enterprise is quoted per deployment via sales. GPUPerHour: Free. Free to use as a price-comparison and research resource; GPUPerHour does not sell GPU capacity itself. The prices shown are third-party provider rates for secure on-demand instances, per GPU-hour, and a companion service (DeployGPU) offers deployment on supported providers.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | An open-source automation powerhouse with deep app connectors, though less specialized for native LLM prompt chaining. | [.md](https://openaitools.app/tool/n8n.md) |
| 2 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | Offers a streamlined no-code builder for deploying custom AI agents, but lacks Dify's open-source flexibility. | [.md](https://openaitools.app/tool/mindstudio.md) |
| 3 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | A self-hosted chat interface for running local LLMs, though lighter on complex visual workflow orchestration. | [.md](https://openaitools.app/tool/open-webui.md) |
| 4 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Provides advanced programmatic frameworks for document parsing and RAG pipelines, but requires coding instead of visual canvases. | [.md](https://openaitools.app/tool/llamaindex.md) |
| 5 | [mcp.so](https://openaitools.app/tool/mcp-server) | 286,704 | -3% | Free | Discover and share Model Context Protocol servers for AI agents and coding tools | [.md](https://openaitools.app/tool/mcp-server.md) |
| 6 | [Activepieces](https://openaitools.app/tool/activepieces) | 258,553 | +1.5% | Freemium | An open-source automation platform combining visual flows with AI steps, though geared more towards general app integration. | [.md](https://openaitools.app/tool/activepieces.md) |
| 7 | [Stork](https://openaitools.app/tool/stork) | 201,544 | +2.3% | Free | AI 工具目录、深度评测与每日 AI 新闻 | [.md](https://openaitools.app/tool/stork.md) |
| 8 | [Models.dev](https://openaitools.app/tool/models-dev) | 200,451 | -3.9% | Free | Open-source database of AI models, prices and capabilities | [.md](https://openaitools.app/tool/models-dev.md) |
| 9 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | Built for scaling multi-agent workforces and B2B task automation, though less focused on open-source RAG pipelines. | [.md](https://openaitools.app/tool/relevance-ai.md) |
| 10 | [FlowHunt](https://openaitools.app/tool/flowhunt-io) | 186,190 | 0% | Free Trial, Paid | Focuses on visual drag-and-drop orchestration for building chatbots and autonomous agents without writing code. | [.md](https://openaitools.app/tool/flowhunt-io.md) |

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Source: https://openaitools.app/compare/dify-ai-vs-gpuperhour

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