# AdminForth vs Qwen 4 (Alibaba Qwen4)

AdminForth records 77 monthly visits with 0% 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 | [AdminForth](https://openaitools.app/tool/adminforth) | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) |
| :--- | :--- | :--- |
| Website URL | https://adminforth.dev | https://qwen.ai |
| Categories | AI Developer Tools, AI Writing Assistants, AI Translate, AI App Builder | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant |
| Pricing Model | Free | Freemium |
| Monthly Visits | 77 | 35,101,353 |
| MoM Growth Rate | 0% | -6.2% |
| Primary Market | Global | Russia |
| Direct Visits | 31 | 25,020,350 |
| Review Score | 4.6 | 4.7 |
| Saved Count | 0 | 1,180 |
| Supported Platforms | Website | Website, API, Open Source |

## AdminForth

AdminForth is an open-source framework for building back-office and admin panels, distributed under the MIT license and designed to be self-hosted inside your own codebase. Rather than locking your data into a proprietary platform, it reads the schema you already have — Postgres, MySQL, SQLite or MongoDB — and renders a complete management interface from a plain declarative resource configuration. Because the resulting panel is just a standard Node.js application with Vue3 components and TailwindCSS styling, it lives in your repo, appears in your code review, and stays fully under your control.

The framework's defining idea is that a back-office should serve two kinds of people who already work with AI: the developer, who can let tools like Claude Code, Codex, Gemini or Copilot write and extend the panel, and the administrator, who can ask an agent to read and update data instead of clicking through pages. AdminForth ships the files coding agents look for (AGENTS.md, CLAUDE.md, llms.txt and a skills directory) so an assistant understands the project without being re-taught each session, and its MCP Server plugin exposes resources and actions as tools that any MCP client can call — each guarded by a revocable secret that runs with the issuing user's permissions, validation and hooks.

Out of the box you get OWASP-compliant sign-in, OAuth2/OpenID SSO adapters for Google, GitHub, Microsoft and Keycloak, RFC 6238 TOTP and WebAuthn passkey two-factor auth, revocable user sessions, audit logging, CSV import/export, file uploads to S3, background jobs, rich text editing, LLM-powered translation and autocomplete, dark mode and custom Vue3 pages and dashboards. Thirty-plus plugins are installed as npm packages with a line of config, and an internal agent plugin can be handed natural-language tasks against your own data. Everything is open, self-hosted and free of seat-based licensing.

**Pricing & Plans:** AdminForth is open source under the MIT license and free to self-host indefinitely — no per-seat or per-panel fees. The project also offers a separate commercial service for teams that want help running it in production.

- **Agent-ready project files:** Every generated app includes AGENTS.md, CLAUDE.md, llms.txt and a skills folder, so Claude Code, Codex, Gemini or Copilot can add resources, columns and plugins without being re-briefed.
- **MCP server & in-panel AI agent:** Expose your resources as remote MCP tools with one revocable secret per agent, and let an internal agent search and edit records using the same permissions, hooks and audit trail.
- **Enterprise-grade auth:** OWASP-compliant sign-in, OAuth2/OpenID SSO adapters for Google, GitHub, Microsoft and Keycloak, RFC 6238 TOTP plus WebAuthn passkeys, and device-level session revocation.
- **Declarative resources over your own DB:** Point AdminForth at Postgres, MySQL, SQLite or MongoDB and describe tables as plain config objects — nothing is copied into a proprietary format.
- **30+ composable plugins:** Audit log, CSV import/export, S3 uploads, background jobs, rich editor, dashboards, LLM translation, LLM autocomplete and bulk AI data generation install as npm packages with a line of config.

**Strengths:** MIT-licensed and self-hosted, so there are no seat fees and no vendor lock-in on your data or schema; Explicitly designed for coding agents and MCP clients, which few admin frameworks address at all; Broad plugin catalog covering SSO, passkeys, audit logs, uploads, background jobs and LLM features; Panel is plain Node.js plus Vue3 and TailwindCSS in your repository, so it stays reviewable and extensible

**Limitations:** Requires Node.js/TypeScript fluency — it is a developer framework, not a no-code admin builder; Some advanced plugins assume PostgreSQL for their own tables, which narrows database choices; Documentation is broad but the pace of plugin additions means some corners are lighter than core guides

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

AdminForth has 77 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?

AdminForth has a month-over-month growth rate of 0%; Qwen 4 (Alibaba Qwen4) has -6.2%.

### How does pricing compare?

AdminForth: Free. AdminForth is open source under the MIT license and free to self-host indefinitely — no per-seat or per-panel fees. The project also offers a separate commercial service for teams that want help running it in production. 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 | [Lovable](https://openaitools.app/tool/lovable) | 31,052,090 | +3.8% | Freemium | Describe your idea in chat and Lovable turns it into a working app or website | [.md](https://openaitools.app/tool/lovable.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 | [Base44](https://openaitools.app/tool/base44) | 14,039,232 | +0.5% | Freemium, Paid, Contact for Pricing | Build working apps, websites, and AI agents by describing them | [.md](https://openaitools.app/tool/base44.md) |
| 6 | [Emergent](https://openaitools.app/tool/emergent) | 5,788,850 | +5% | Freemium | Describe an app in chat and ship it | [.md](https://openaitools.app/tool/emergent.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 10 | [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) |

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

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