# Qwen 4 (Alibaba Qwen4) vs Text2SQL.AI

Qwen 4 (Alibaba Qwen4) records 35,101,353 monthly visits with -6.2% month-over-month growth and Freemium pricing. Text2SQL.AI records 0 monthly visits with — growth and Freemium, Paid pricing.

| Metric | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | [Text2SQL.AI](https://openaitools.app/tool/text2sql-ai) |
| :--- | :--- | :--- |
| Website URL | https://qwen.ai | https://text2sql.lemonsqueezy.com |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant | SQL Query Builder, AI Code Generator, AI Assistant, AI API |
| Pricing Model | Freemium | Freemium, Paid |
| Monthly Visits | 35,101,353 | 0 |
| MoM Growth Rate | -6.2% | — |
| Primary Market | Russia | Global |
| Direct Visits | 25,020,350 | 0 |
| Review Score | 4.7 | 4.4 |
| Saved Count | 1,180 | 4 |
| 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)

## Text2SQL.AI

Text2SQL.AI is an AI query generator that turns natural-language questions into working SQL. Instead of wrestling with syntax, users describe what they need in plain language and receive an optimized query within seconds, then ask follow-ups until the result is right. Adding a schema with tables, columns, and relationships helps the model produce queries that fit a specific database design.

The tool covers all major SQL and NoSQL databases, including MySQL, PostgreSQL, Oracle PL/SQL, and Microsoft SQL Server, adapting to the syntax and features of each engine. Beyond the generator, it offers a public API for embedding text-to-SQL in other products, ancillary generators for Excel and Sheets formulas and regex, and helper features for fixing, explaining, and optimizing SQL. An Insights view consolidates the query, result table, chart, and explanation in one screen with version control.

Text2SQL.AI reports more than 256,000 users and is used by engineers and analysts at companies like Vercel and Google, per testimonials. It offers a free starting tier plus Pro subscriptions that include a cross-platform desktop app for Windows, macOS, and Linux, where database credentials can stay local. Pricing tiers have been listed from around $7 to $228 depending on plan length.

**Pricing & Plans:** Freemium with a free starting tier and paid Pro subscriptions. Listed prices have ranged roughly from $7 to $48 for the base tier and $29 to $228 for Pro, depending on billing term; the desktop app is included with Pro.

- **Natural Language to SQL:** Describe what you want in everyday language and get an optimized SQL query in seconds, then refine with follow-up questions.
- **Schema-Aware Accuracy:** Add your tables, columns, and relationships so the AI generates queries that match your actual database design.
- **Broad Database Support:** Generate queries for MySQL, PostgreSQL, Oracle PL/SQL, Microsoft SQL Server, and other major SQL and NoSQL systems.
- **Public API:** Integrate text-to-SQL generation into your own products and workflows through a documented public API.
- **Insights Workspace:** Ask a question and get the SQL, result table, auto-generated chart, and explanation in a single unified view with query version control.

**Strengths:** Turns plain-language questions into usable SQL in seconds, cutting time spent on syntax.; Schema input noticeably improves accuracy and fit to a real database.; Wide database coverage, from MySQL and PostgreSQL to Oracle PL/SQL and SQL Server.; Desktop app option keeps credentials and data local for privacy-conscious teams.

**Limitations:** Complex or unusual schema logic can still require manual review of generated queries.; Advanced usage depends on a paid Pro plan and API limits vary by tier.; Best results require maintaining accurate schema definitions.

[Profile (Markdown)](https://openaitools.app/tool/text2sql-ai.md)

## Frequently Asked Questions

### How do Qwen 4 (Alibaba Qwen4) and Text2SQL.AI compare in monthly traffic?

Qwen 4 (Alibaba Qwen4) has 35,101,353 monthly visits, while Text2SQL.AI has 0. 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%; Text2SQL.AI has —.

### 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). Text2SQL.AI: Freemium, Paid. Freemium with a free starting tier and paid Pro subscriptions. Listed prices have ranged roughly from $7 to $48 for the base tier and $29 to $228 for Pro, depending on billing term; the desktop app is included with Pro.

## 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/qwen-4-vs-text2sql-ai

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