# Qwen 4 (Alibaba Qwen4) vs sshx

Qwen 4 (Alibaba Qwen4) records 35,101,353 monthly visits with -6.2% month-over-month growth and Freemium pricing. sshx records 13,059 monthly visits with +43.1% growth and Free pricing.

| Metric | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | [sshx](https://openaitools.app/tool/sshx) |
| :--- | :--- | :--- |
| Website URL | https://qwen.ai | https://sshx.io |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant | Other |
| Pricing Model | Freemium | Free |
| Monthly Visits | 35,101,353 | 13,059 |
| MoM Growth Rate | -6.2% | +43.1% |
| Primary Market | Russia | India |
| Direct Visits | 25,020,350 | 8,701 |
| Review Score | 4.7 | 4.6 |
| Saved Count | 1,180 | 1 |
| 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)

## sshx

sshx takes the awkwardness out of showing someone your terminal. Instead of screen sharing a whole desktop or walking a colleague through pasting output into chat, you install a small client, run it inside the shell you want to share, and it hands back a browser link. Whoever needs to look — a teammate, a student, an on-call engineer — opens that link and joins the same live session, complete with their own cursor.

The interface is deliberately collaborative. Sessions open on an infinite canvas that you can pan and zoom, and each terminal can be moved, resized and duplicated, so a debugging call with four people does not dissolve into confusion about which window is which. Participant names, cursors and a chat pane sit alongside the terminal itself. Because the transport is end-to-end encrypted and the server is only a relay, the operator of the infrastructure cannot read what is being typed.

sshx is free and open source, written with a Rust server to keep it responsive over a global mesh network. Typical uses are pair programming and debugging, live teaching, incident response across time zones, and reaching a shell on a cloud VM or CI runner without handing out SSH keys. Installs are one line on macOS and Linux, with prebuilt binaries for Windows, Linux ARM variants and FreeBSD, plus a GitHub Actions mode that pauses a workflow and opens the session for inspection.

**Pricing & Plans:** Free. sshx is an open-source project with no paid plans advertised; you install the client and share sessions at no cost.

- **Share a terminal by link:** Run one command and sshx prints a unique link. Sharing that link is all it takes to give someone a live, interactive view of your terminal.
- **Real-time collaboration and chat:** Multiple people can work in the same session at once, with visible names and remote cursors so you always know who is typing where.
- **Infinite canvas workspace:** Terminals live on a multiplayer infinite canvas that you can pan, zoom, move and resize, so you can arrange many sessions like a whiteboard.
- **End-to-end encryption:** Session data is encrypted end to end, meaning the relay server in the middle never sees the commands or output you exchange.
- **Fast mesh networking:** A lightweight server written in Rust and a distributed peer network route your session to the nearest node for low-latency typing.
- **Cross-platform and open source:** The command-line client runs on macOS, Linux, Windows and FreeBSD, and the source is open for self-hosting or inspection.

**Strengths:** Faster and less invasive than sharing your whole screen; Nothing to install for the people you invite — a browser link is enough; End-to-end encryption means the relay server never sees session contents; The infinite canvas keeps multi-terminal, multi-person sessions readable

**Limitations:** It is a terminal-sharing layer, not a full remote-desktop or IDE experience; No built-in access control beyond the secret URL — anyone with the link can join; Feature scope is intentionally narrow; there is no built-in file browser, session recording suite or enterprise SSO; Self-hosting the server requires familiarity with Rust and the project's deployment model

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

## Frequently Asked Questions

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

Qwen 4 (Alibaba Qwen4) has 35,101,353 monthly visits, while sshx has 13,059. 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%; sshx has +43.1%.

### 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). sshx: Free. Free. sshx is an open-source project with no paid plans advertised; you install the client and share sessions at no cost.

## 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 | [Duck.ai](https://openaitools.app/tool/duck-ai) | 26,431,539 | +10.7% | Free | Private AI chat from the makers of DuckDuckGo | [.md](https://openaitools.app/tool/duck-ai.md) |
| 4 | [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) |
| 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 | [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 | [Pi Coding Agent](https://openaitools.app/tool/pi-coding-agent) | 1,929,244 | +4% | Free | A minimal, extensible terminal coding agent you can reshape | [.md](https://openaitools.app/tool/pi-coding-agent.md) |
| 9 | [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) |
| 10 | [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) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)