# Qwen 4 (Alibaba Qwen4) vs Scalebrowser

Qwen 4 (Alibaba Qwen4) records 35,101,353 monthly visits with -6.2% month-over-month growth and Freemium pricing. Scalebrowser records 161,955 monthly visits with +212.7% growth and Free Trial, Paid pricing.

| Metric | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | [Scalebrowser](https://openaitools.app/tool/scalebrowser) |
| :--- | :--- | :--- |
| Website URL | https://qwen.ai | https://scalebrowser.net |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant | AI Browsers, AI Agent, AI Developer Tools, AI API |
| Pricing Model | Freemium | Free Trial, Paid |
| Monthly Visits | 35,101,353 | 161,955 |
| MoM Growth Rate | -6.2% | +212.7% |
| Primary Market | Russia | Global |
| Direct Visits | 25,020,350 | 65,234 |
| Review Score | 4.7 | 4.7 |
| Saved Count | 1,180 | 0 |
| Supported Platforms | Website, API, Open Source | Website |

## 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)

## Scalebrowser

>Scalebrowser targets the part of agent work that usually breaks first: staying authenticated. Instead of scraping a signed-out page or re-logging in on every run, it hands each agent a browser machine that keeps a stable identity, complete with stored passwords, per-profile inboxes, two-factor codes and passkeys. The product installs as a desktop app so the GPU, screen and fingerprint values match the real machine, which reduces the chance that a profile contradicts itself.

On top of the browser layer, Scalebrowser adds an agent layer. Agents read a page once and then only what changed, which keeps token spend predictable on long runs. Captchas are handled through human-like input, keys on a page are surfaced to the agent as placeholders, and each tool call is logged as a step with a result and a screenshot. It works with MCP clients such as Claude and Cursor, Python and Node SDKs, a REST API and direct CDP for existing browser-use code.

Plans are measured by how much runs at once. The free tier covers a single browser and three profiles, while paid tiers grow concurrent browsers, machines, profiles and workflows. Workflows can be started by hand or by an agent, and higher tiers add schedules, webhooks, sync and phone approvals.

**Pricing & Plans:** Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial.

- **Persistent profile identity:** Each profile is generated from a seed so its identity, cookies and logins persist across restarts, and sites see the same returning visitor rather than a new device.
- **Isolated browser profiles:** One browser per profile means separate logins, cookies and devices that share nothing, making multi-account automation safe to run in parallel.
- **Built-in sign-in and 2FA handling:** Agents get through username and password forms, email confirmation codes, TOTP and SMS two-factor codes, passkeys and permission prompts without stalling.
- **Human-like input and captchas:** Press-and-hold, image grid, slider and rotation captchas are solved through human-like input rather than third-party solving keys.
- **Flexible agent integrations and trails:** Connect over MCP, Python or Node SDKs, REST or direct CDP, and review every action as a step with its result and screenshot.

**Strengths:** Strong focus on persistent, isolated identities so agents stay logged in across runs; Broad integration surface covering MCP, Python/Node SDKs, REST and direct CDP; Built-in handling of logins, email codes, TOTP, SMS, passkeys and captchas; Token-efficient page reading that only reports what changed between steps

**Limitations:** Requires installing a desktop app and running it on your own machine, so it is not a purely cloud-hosted service; Free tier excludes schedules, webhooks, sync and phone approvals; Paid tiers meter concurrent browsers, machines and profile counts, which can raise costs for large fleets; Advanced anti-detection features may raise compliance responsibility with target platforms

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

## Frequently Asked Questions

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

Qwen 4 (Alibaba Qwen4) has 35,101,353 monthly visits, while Scalebrowser has 161,955. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Qwen 4 (Alibaba Qwen4) has a month-over-month growth rate of -6.2%; Scalebrowser has +212.7%.

### How does pricing compare?

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). Scalebrowser: Free Trial, Paid. Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial.

## 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 | [Apify](https://openaitools.app/tool/apify) | 4,147,762 | +3.9% | Freemium, Contact for Pricing | A massive cloud web scraping and automation marketplace, though it lacks Scalebrowser's focus on persistent isolated profiles. | [.md](https://openaitools.app/tool/apify.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 10 | [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) |

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

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