# GPUPerHour vs Qwen 4 (Alibaba Qwen4)

GPUPerHour records 28,718 monthly visits with +25.3% month-over-month growth and Free pricing. Qwen 4 (Alibaba Qwen4) records 35,101,353 monthly visits with -6.2% growth and Freemium pricing.

| Metric | [GPUPerHour](https://openaitools.app/tool/gpuperhour) | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) |
| :--- | :--- | :--- |
| Website URL | https://gpuperhour.com | https://qwen.ai |
| Categories | AI Developer Tools, AI Tools Directory | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant |
| Pricing Model | Free | Freemium |
| Monthly Visits | 28,718 | 35,101,353 |
| MoM Growth Rate | +25.3% | -6.2% |
| Primary Market | United States | Russia |
| Direct Visits | 11,398 | 25,020,350 |
| Review Score | 4.4 | 4.7 |
| Saved Count | 4 | 1,180 |
| Supported Platforms | Website | Website, API, Open Source |

## 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)

## Qwen 4 (Alibaba Qwen4)

Qwen 4 (also known as Qwen4 or Tongyi Qianwen 4) is Alibaba Cloud's fourth-generation foundation model family and multimodal AI assistant platform accessible at qwen.ai and chat.qwen.ai. Formally unveiled in training at the Hangzhou Apsara Conference on September 22, 2026 and detailed on stage at Apsara Amsterdam on October 29, 2026, Qwen 4 spearheads Alibaba's full-stack AI roadmap that scales toward 5 to 10 trillion parameters in the upcoming Qwen 4.5 and Qwen 5 generations.

The Qwen 4 series is organized into four core deployment tiers—Qwen4-Max (flagship frontier reasoning model), Qwen4-Plus (balanced enterprise API workhorse), Qwen4-Flash (low-latency, high-throughput model), and Qwen4-27B (a 27-billion-parameter open-weight model engineered to run locally on consumer PCs and single-GPU workstations)—alongside specialized variants spotted in official Qwen Code repositories such as qwen4-coder-plus and qwen4-omni-120b-think. Architecturally, Qwen 4 builds on the foundation previewed in August 2026's Qwen3.8-Flash-Next: a hybrid Gated DeltaNet + Gated Attention sparse Mixture-of-Experts (MoE) design (125B total parameters with just 6B active per token and a 51B n-gram embedding lookup layer) paired with a 1-million-token context window and Recursive Self-Improvement (RSI) post-training.

For developers, enterprises, and everyday users, the Qwen platform offers a completely free web and mobile workspace at chat.qwen.ai featuring Deep Research, Web Dev Artifacts, live search, and native image/video/audio generation (Qwen-Image 3.1 and Qwen-Audio 3.1), while open-weight checkpoints are distributed on Hugging Face, ModelScope, and Ollama alongside commercial API hosting on Alibaba Cloud Model Studio.

**Pricing & Plans:** Free multimodal web & mobile chat at chat.qwen.ai; Apache 2.0 open-weight local models (Qwen4-27B & Qwen3.8-Flash-Next architecture preview) free on Hugging Face and Ollama; commercial API on Alibaba Cloud Model Studio (~$0.15 / $0.47 per 1M tokens on Flash tiers and ~$2.00 / $6.00 per 1M tokens on Max tiers).

- **Four-Tier Qwen 4 Model Lineup (Max, Plus, Flash & 27B):** Covers every compute envelope from the multi-trillion-scale Qwen4-Max flagship and Qwen4-Plus/Flash APIs to the local PC-friendly Qwen4-27B open-weight checkpoint, plus qwen4-coder-plus and qwen4-omni-120b-think.
- **Hybrid Gated DeltaNet + Sparse MoE & N-Gram Memory:** Pioneered in the Qwen3.8-Flash-Next architecture preview, combining ultra-lean active parameter routing (6B active out of 125B) with a 51B n-gram embedding layer that trades compute for instant memorized lookup.
- **1-Million-Token Context Window Across Modalities:** Sizes the Qwen 4 generation at a full 1M-token context window across text, code, images, audio, and video for repository-wide coding and cross-document reasoning.
- **Recursive Self-Improvement (RSI) & Agentic Tool Use:** Trained via multi-cycle automated Recursive Self-Improvement across coding, math, and hardware EDA workflows—demonstrating 10,000+ autonomous tool calls in chip design and software engineering.
- **Free Qwen Chat Workspace & Open-Weight Ecosystem:** Provides free access at chat.qwen.ai with Web Dev Artifacts, Deep Research, Qwen-Image 3.1, and Qwen-Audio 3.1, plus one-command local deployment via Ollama, vLLM, and Hugging Face.

**Strengths:** Complete 4-tier ecosystem spanning cloud flagships (Qwen4-Max/Plus/Flash) and consumer-GPU open weights (Qwen4-27B); Breakthrough Gated DeltaNet + 51B n-gram memory MoE architecture delivers frontier quality at a fraction of active inference compute; 1-million-token context window and native multimodal support across text, code, vision, audio, and video; Free full-featured web assistant at chat.qwen.ai with no mandatory subscription wall for everyday research and coding

**Limitations:** Staged late-2026 rollout following Apsara Hangzhou (Sept 22) and Amsterdam (Oct 29) means flagship Qwen4-Max weights and APIs release progressively after the Qwen3.8-Flash-Next architecture preview; Largest Qwen4-Max and upcoming 5–10T parameter Qwen 4.5/5 models require cloud APIs or multi-node enterprise GPU clusters; Brand split between international Qwen (qwen.ai / Model Studio) and domestic Tongyi Qianwen can confuse first-time API adopters

[Profile (Markdown)](https://openaitools.app/tool/qwen-4.md)

## Frequently Asked Questions

### How do GPUPerHour and Qwen 4 (Alibaba Qwen4) compare in monthly traffic?

GPUPerHour has 28,718 monthly visits, while Qwen 4 (Alibaba Qwen4) has 35,101,353. 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%; Qwen 4 (Alibaba Qwen4) has -6.2%.

### 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. Qwen 4 (Alibaba Qwen4): Freemium. Free multimodal web & mobile chat at chat.qwen.ai; Apache 2.0 open-weight local models (Qwen4-27B & Qwen3.8-Flash-Next architecture preview) free on Hugging Face and Ollama; commercial API on Alibaba Cloud Model Studio (~$0.15 / $0.47 per 1M tokens on Flash tiers and ~$2.00 / $6.00 per 1M tokens on Max tiers).

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | Provides state-of-the-art open-weight reasoning models and low-cost APIs, but with less emphasis on multimodal Alibaba ecosystem tools. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides robust developer tools and multimodal APIs, but relies on Google's closed Gemini models rather than open-weight alternatives. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 3 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Aggregates hundreds of models behind one API gateway, but functions as a router rather than hosting native Qwen infrastructure. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 4 | [BigModel](https://openaitools.app/tool/bigmodel) | 5,700,686 | -17% | Freemium | Offers competing Chinese foundation model APIs and agent builders, but specializes in Zhipu AI's GLM architecture. | [.md](https://openaitools.app/tool/bigmodel.md) |
| 5 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Provides lightweight open-weight models for local deployment, but offers smaller parameter sizes compared to top-tier Qwen variants. | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) |
| 6 | [Groq](https://openaitools.app/tool/groq) | 3,987,936 | +10% | Paid | Delivers ultra-fast inference speeds using custom LPU hardware, but supports a more limited selection of open models. | [.md](https://openaitools.app/tool/groq.md) |
| 7 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Offers robust serverless APIs for open-source models, but lacks native training integrations specific to Alibaba's ecosystem. | [.md](https://openaitools.app/tool/together-ai.md) |
| 8 | [Tencent Hunyuan](https://openaitools.app/tool/tencent-hunyuan-large-model) | 1,485,463 | -1.2% | Contact for Pricing | Provides comparable multimodal foundation model APIs from a major tech giant, but utilizes Tencent's proprietary Hunyuan architecture. | [.md](https://openaitools.app/tool/tencent-hunyuan-large-model.md) |
| 9 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Specializes in memory-efficient fine-tuning for open-weight models, but requires external infrastructure to deploy full production APIs. | [.md](https://openaitools.app/tool/unsloth-ai.md) |
| 10 | [Fireworks](https://openaitools.app/tool/fireworks-ai) | 659,687 | +6% | Contact for Pricing | Delivers exceptionally high-throughput inference for open-weight models, but focuses more on general open-source deployment than Qwen-specific tools. | [.md](https://openaitools.app/tool/fireworks-ai.md) |

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Source: https://openaitools.app/compare/gpuperhour-vs-qwen-4

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