# GPUPerHour vs LiteLLM GPUPerHour records 28,718 monthly visits with +25.3% month-over-month growth and Free pricing. LiteLLM records 576,967 monthly visits with +7.9% growth and Freemium, Contact for Pricing pricing. | Metric | [GPUPerHour](https://openaitools.app/tool/gpuperhour) | [LiteLLM](https://openaitools.app/tool/litellm) | | :--- | :--- | :--- | | Website URL | https://gpuperhour.com | https://litellm.ai | | Categories | AI Developer Tools, AI Tools Directory | AI API, Large Language Models (LLMs), AI Developer Tools, Open Source AI Models | | Pricing Model | Free | Freemium, Contact for Pricing | | Monthly Visits | 28,718 | 576,967 | | MoM Growth Rate | +25.3% | +7.9% | | Primary Market | United States | United States | | Direct Visits | 11,398 | 228,967 | | Review Score | 4.4 | 4.8 | | Saved Count | 4 | 5 | | Supported Platforms | Website | Website | ## 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) ## LiteLLM LiteLLM is an open-source AI gateway and Python SDK designed to remove vendor lock-in from LLM applications. The SDK lets you call models from OpenAI, Anthropic, Google Vertex AI, Bedrock, Mistral, Azure and dozens of other providers using the same OpenAI-style request format, so switching models is a configuration change rather than a code rewrite. The same project ships an AI Gateway (often called the proxy) that turns that abstraction into a shared service for an entire organization. That gateway is where most platform teams find the value. It issues virtual keys scoped by team, project or application, tracks spend per key against budgets, applies rate limits (TPM and RPM), and exposes dashboards for request volume, token usage and cost per model. Routing features include load balancing across deployments, automatic fallbacks when a provider fails, retries and budget-based rerouting, plus guardrails for PII masking, prompt-injection detection and secret detection. The project is genuinely open source with the code on GitHub (BerriAI/litellm) and a very active community. Enterprise features add SSO, audit logs, and support for agents and MCP servers through the same gateway. Notably, LiteLLM supports day-zero access to new models so teams can adopt them as soon as they ship, and it can also serve self-hosted, fine-tuned and internal models behind the same key. Companies cited on the site include NVIDIA, Netflix, Okta, Lemonade and AT&T. **Pricing & Plans:** Freemium and open source. The self-hosted LiteLLM gateway and SDK are free under an open-source licence, and a free tier lets you get started immediately. Enterprise plans with SSO, audit logs, SLAs and advanced support are quoted on request via the sales team. - **OpenAI-compatible API for 100+ LLMs:** Call 100+ providers and 1,800+ models using one request format, so you can swap models without changing application code. - **Virtual keys, teams and budgets:** Issue scoped keys per team, project or app, set monthly spend caps and see exactly who is driving usage and cost. - **Routing, load balancing and fallbacks:** Distribute traffic across deployments, retry on failure and automatically fall back to another model or provider when one goes down. - **Observability and spend tracking:** Dashboards for request volume, tokens and cost per model, with support for logging and analytics integrations. - **Guardrails and policy controls:** Plug in PII masking, prompt-injection detection and secret-detection guardrails, and manage policies centrally instead of in every app. **Strengths:** Truly open source with a large GitHub community and self-hosting option; Very broad provider coverage with an OpenAI-compatible interface; Enterprise-grade controls: virtual keys, budgets, rate limits and audit logs; Day-zero support for new models and easy fallback when providers fail **Limitations:** Self-hosting means you own deployment, upgrades and uptime; Feature depth varies between the free open-source version and enterprise plan; The breadth of configuration options can be overwhelming for small projects [Profile (Markdown)](https://openaitools.app/tool/litellm.md) ## Frequently Asked Questions ### How do GPUPerHour and LiteLLM compare in monthly traffic? GPUPerHour has 28,718 monthly visits, while LiteLLM has 576,967. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? GPUPerHour has a month-over-month growth rate of +25.3%; LiteLLM has +7.9%. ### How does pricing compare? 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. LiteLLM: Freemium, Contact for Pricing. Freemium and open source. The self-hosted LiteLLM gateway and SDK are free under an open-source licence, and a free tier lets you get started immediately. Enterprise plans with SSO, audit logs, SLAs and advanced support are quoted on request via the sales team. ## 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 massive hosted model catalog with instant access, but requires trusting a third-party platform instead of self-hosting. | [.md](https://openaitools.app/tool/openrouter-ai.md) | | 2 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Hosts high-performance open-weight models directly on dedicated serverless infrastructure, but does not route across external providers. | [.md](https://openaitools.app/tool/together-ai.md) | | 3 | [OrcaRouter](https://openaitools.app/tool/orcarouter) | 975,300 | -5.2% | Freemium | Delivers automated model failover and budget governance through an API gateway, but with less open-source customization. | [.md](https://openaitools.app/tool/orcarouter.md) | | 4 | [ZenMux](https://openaitools.app/tool/zenmux) | 444,394 | +16.7% | Freemium, Paid | Unified LLM gateway with failover and analytics, but offers less robust open-source developer SDK support. | [.md](https://openaitools.app/tool/zenmux.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 | [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) | | 7 | [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) | | 8 | [Portkey](https://openaitools.app/tool/portkey-ai) | 195,650 | -9.4% | Freemium, Paid, Contact for Pricing | Offers advanced enterprise observability and guardrail tools, but lacks LiteLLM's lightweight self-hosted proxy simplicity. | [.md](https://openaitools.app/tool/portkey-ai.md) | | 9 | [Eden AI](https://openaitools.app/tool/eden-ai) | 173,828 | +6.5% | Paid, Contact for Pricing | Provides managed multi-provider AI routing and cost tracking, but lacks the native open-source flexibility of LiteLLM. | [.md](https://openaitools.app/tool/eden-ai.md) | | 10 | [LLM Gateway](https://openaitools.app/tool/llm-gateway) | 168,426 | -14.5% | Freemium, Contact for Pricing | An open-source alternative for unifying LLM providers, but features a less extensive ecosystem of middleware integrations. | [.md](https://openaitools.app/tool/llm-gateway.md) | --- Source: https://openaitools.app/compare/gpuperhour-vs-litellm More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)