# NativeMind vs Qwen 4 (Alibaba Qwen4)

NativeMind records 2,207 monthly visits with -54.1% 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 | [NativeMind](https://openaitools.app/tool/nativemind) | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) |
| :--- | :--- | :--- |
| Website URL | https://nativemind.app | https://qwen.ai |
| Categories | AI Assistant, AI Browsers, AI Summarizer, AI Search Engine | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant |
| Pricing Model | Free | Freemium |
| Monthly Visits | 2,207 | 35,101,353 |
| MoM Growth Rate | -54.1% | -6.2% |
| Primary Market | United States | Russia |
| Direct Visits | 850 | 25,020,350 |
| Review Score | 4.4 | 4.7 |
| Saved Count | 0 | 1,180 |
| Supported Platforms | Website | Website, API, Open Source |

## NativeMind

NativeMind is a browser extension built around a single idea: your AI should run on your machine, not someone else's server. It connects to local models served through Ollama — including gpt-oss, DeepSeek, Qwen, Llama, Gemma and Mistral — so you get an assistant that works inside the pages you already use without transmitting a single byte of your data to the cloud.

Instead of a separate chat app, NativeMind lives in the browser and understands context. You can add open tabs to a conversation, upload local PDFs, images or screenshots for private analysis, and translate full pages while preserving their layout. Its autonomous Agent Mode uses on-device tools such as local web search and file analysis to complete multi-step tasks, and a lightweight in-page API lets developers call their local LLM from their own web apps without an SDK or server.

NativeMind also embeds into everyday workflows: it acts as a Gmail assistant for summarizing and drafting replies, and provides writing tools for refining text anywhere on the web. Personal use is completely free, with no sign-up and no tracking. The project is open source, auditable and community-backed, with a GitHub repository and Discord community behind it. Because everything runs locally, the practical requirement is a reasonably capable machine, and a GPU helps for larger models.

**Pricing & Plans:** NativeMind is free for personal use — no sign-up, no tracking. You provide the local models via Ollama, and any hardware costs are your own.

- **Local LLM via Ollama:** Load and switch between open models such as gpt-oss, DeepSeek, Qwen, Llama, Gemma and Mistral instantly, with no cloud round-trip.
- **Privacy by default:** Prompts, page content and uploaded files never leave your device — NativeMind does not track, store or transmit your data.
- **Agent Mode with on-device tools:** An autonomous agent uses local web search and file analysis to carry out multi-step research and tasks securely.
- **Chat across tabs, PDFs and images:** Add open browser tabs as context, or upload local PDFs, images and screenshots for private analysis and summarization.
- **Embedded writing and translation:** Summarize emails, refine writing anywhere on the page, and translate entire pages while keeping their layout intact.

**Strengths:** Completely free for personal use with no account required; All processing stays on-device, so nothing is sent to the cloud; Open source and auditable, backed by a GitHub repo and community; Works across pages, PDFs, images, Gmail and full-page translation

**Limitations:** Requires you to install and manage Ollama and local models yourself; Performance depends heavily on your hardware; large models benefit from a GPU; Newer agent and API features are still maturing compared with cloud assistants

[Profile (Markdown)](https://openaitools.app/tool/nativemind.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 NativeMind and Qwen 4 (Alibaba Qwen4) compare in monthly traffic?

NativeMind has 2,207 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?

NativeMind has a month-over-month growth rate of -54.1%; Qwen 4 (Alibaba Qwen4) has -6.2%.

### How does pricing compare?

NativeMind: Free. NativeMind is free for personal use — no sign-up, no tracking. You provide the local models via Ollama, and any hardware costs are your own. 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 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) |
| 5 | [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) |
| 6 | [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) |
| 7 | [Kagi Search](https://openaitools.app/tool/kagi-search) | 4,647,605 | +3.2% | Free Trial, Paid | A paid, ad-free search engine that answers to its users | [.md](https://openaitools.app/tool/kagi-search.md) |
| 8 | [Monica](https://openaitools.app/tool/monica-ai) | 4,512,775 | -11.3% | Freemium | All-in-one AI assistant across web, browser, desktop and mobile | [.md](https://openaitools.app/tool/monica-ai.md) |
| 9 | [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) |
| 10 | [Sider](https://openaitools.app/tool/sider) | 2,644,740 | -10.6% | Freemium | AI sidebar and browser agent for reading, writing and research | [.md](https://openaitools.app/tool/sider.md) |

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

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