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Zelili AI

Qwen3

From Alibaba Cloud

Alibaba’s Flagship Open-Source LLM Family – Massive Scale Reasoning, Multilingual Mastery, and Efficient MoE Architecture
Tool Release Date

28 Apr 2025

Tool Users
700 Million+
0.0

Pricing Model

Starting Price

$0/Month

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About This AI

Qwen3 is Alibaba’s latest generation large language model series released in April 2025, featuring both dense and Mixture-of-Experts (MoE) variants with up to 235 billion total parameters (22B active in flagship MoE).

Trained on 36 trillion tokens across 119 languages and dialects, it delivers superior performance in reasoning, instruction following, tool use, multilingual tasks, coding, math, and general capabilities.

Key models include dense sizes (0.6B to 32B) and MoE (30B-A3B, 235B-A22B), with context windows up to 128K tokens (some variants extended further).

Qwen3 supports hybrid thinking modes (enable/disable reasoning via tokenizer), agentic workflows, reduced hallucinations, and strong benchmark results rivaling top models like DeepSeek-R1, o1, Grok-3, and Gemini-2.5-Pro.

Subsequent releases like Qwen3-Max (September 2025, >1 trillion parameters reported), Qwen3-Next (September 2025, hybrid attention and sparse MoE), and specialized variants (e.g., Qwen3-Coder, Qwen3-ASR) extend capabilities to coding, speech, vision, and more.

Fully open-sourced under Apache 2.0 for most models, available on Hugging Face, ModelScope, and chat.qwen.ai for free use.

API access via Alibaba Cloud (token-based pricing) and third-party providers offers cost-effective inference.

With over 700 million cumulative downloads on Hugging Face by January 2026, Qwen3 leads global open-source AI adoption, powering chat assistants, developers, enterprises, and research worldwide.

Key Features

  1. Dense and MoE variants: From 0.6B to 235B total parameters with efficient active parameter usage in MoE models
  2. Multilingual excellence: Trained on 119 languages/dialects for superior non-English performance
  3. Hybrid reasoning modes: Toggle thinking/non-thinking via tokenizer for balanced speed vs depth
  4. Agentic capabilities: Strong tool use, multi-step planning, and workflow execution
  5. Long context support: Up to 128K tokens (extended in later variants) for document-heavy tasks
  6. High benchmark performance: Competitive or leading in coding, math, reasoning, and general knowledge
  7. Open-source accessibility: Apache 2.0 license for most models with weights on Hugging Face/ModelScope
  8. API and chat integration: Free chat.qwen.ai interface plus affordable token-based API
  9. Specialized extensions: Variants for coding (Qwen3-Coder), speech (Qwen3-ASR/TTS), vision, and more
  10. Efficient inference: MoE design enables high throughput and lower compute costs

Price Plans

  1. Free ($0): Full open-source models (weights/code) for download and local use; free chat access at chat.qwen.ai with limits; basic API trials
  2. API Paid (Token-based ~$0.07 to $1.60 per million input tokens depending on provider/model): Usage pricing via Alibaba Cloud, Groq, DeepInfra, OpenRouter, etc.; varies by variant and volume
  3. Enterprise (Custom): Dedicated hosting, higher limits, support, and fine-tuning options through Alibaba Cloud

Pros

  1. Leading open-source adoption: Over 700 million downloads by early 2026, most downloaded AI family globally
  2. Exceptional multilingual strength: Outperforms many rivals in non-English languages and dialects
  3. Cost-effective scale: MoE models deliver high performance with fraction of active parameters
  4. Strong reasoning and agents: Competitive with proprietary leaders in complex tasks
  5. Full open weights: Apache 2.0 allows free commercial use, fine-tuning, and local deployment
  6. Rapid iteration: Frequent updates with specialized models and architecture improvements
  7. Free chat access: Powerful interface at chat.qwen.ai with no subscription required
  8. Developer-friendly: Easy integration via Hugging Face, ModelScope, and OpenAI-compatible API

Cons

  1. API pricing for heavy use: Token-based costs apply via Alibaba Cloud or third-parties for production-scale inference
  2. Hardware demands: Largest models require significant GPU resources for local running
  3. Knowledge cutoff: Base training ends before very recent events (post-April 2025 updates add real-time search)
  4. Variable third-party costs: Pricing differs across providers (e.g., Groq, DeepInfra)
  5. Setup for local use: Requires technical expertise and compute for full open weights deployment
  6. Less multimodal in base: Core text focus; vision/audio in specialized variants
  7. Competition intensity: Rapidly evolving space with frequent rival releases

Use Cases

  1. Multilingual chat and assistance: Powering global AI companions with strong non-English support
  2. Coding and software development: Generating, debugging, and refactoring code with Qwen3-Coder variants
  3. Research and analysis: Summarizing long documents, reasoning over complex data, math/science tasks
  4. Agent automation: Building multi-step agents for workflows, tool calling, and planning
  5. Content creation: Writing, translation, creative generation in 119 languages
  6. Enterprise applications: Custom fine-tuned models for business intelligence, customer support
  7. Local/offline deployment: Running open weights on private infrastructure for privacy

Target Audience

  1. Developers and researchers: Fine-tuning, local deployment, and extending open models
  2. Global enterprises: Needing multilingual, cost-effective, high-performance LLMs
  3. Non-English users: Benefiting from superior coverage in 119 languages/dialects
  4. AI hobbyists: Free access via chat.qwen.ai and Hugging Face
  5. Coding professionals: Leveraging specialized Qwen3-Coder for development tasks
  6. Business teams: Integrating via API for productivity, automation, and analytics

How To Use

  1. Chat interface: Visit chat.qwen.ai, start typing prompts; no signup needed for basic use
  2. Download open models: Go to Hugging Face or ModelScope, search 'Qwen/Qwen3', download weights
  3. Local inference: Use transformers or vLLM libraries; load model with from_pretrained()
  4. API access: Sign up at Alibaba Cloud or third-party (Groq, DeepInfra), get API key, call endpoints
  5. Reasoning mode: Enable thinking via tokenizer or prompt (e.g., 'think step by step')
  6. Multimodal variants: Use specialized models (e.g., Qwen3-VL) for image/audio inputs
  7. Fine-tuning: Leverage open weights with tools like Axolotl or Llama-Factory

How we rated Qwen3

  • Performance: 4.8/5
  • Accuracy: 4.7/5
  • Features: 4.9/5
  • Cost-Efficiency: 4.9/5
  • Ease of Use: 4.6/5
  • Customization: 4.8/5
  • Data Privacy: 4.7/5
  • Support: 4.5/5
  • Integration: 4.7/5
  • Overall Score: 4.8/5

Qwen3 integration with other tools

  1. Hugging Face: Model weights, inference demos, and community fine-tunes hosted for easy access
  2. Alibaba Cloud Model Studio: API platform with OpenAI-compatible endpoints and enterprise tools
  3. Third-Party Providers: Groq, DeepInfra, OpenRouter for fast/cost-effective inference
  4. Local Frameworks: Compatible with vLLM, transformers, Ollama for deployment and serving
  5. Chat Platforms: Powers chat.qwen.ai web/app with seamless user experience

Best prompts optimised for Qwen3

  1. Solve this complex math problem step by step with clear reasoning: [insert problem]
  2. Write a detailed Python script for a web scraper that handles pagination and login, explain each part
  3. Translate this technical document from Chinese to English with precise terminology preserved: [insert text]
  4. Act as an expert financial analyst and evaluate this company based on the provided data: [insert financials]
  5. Generate a creative story in anime style about a cyberpunk city adventure, include vivid descriptions
Qwen3 stands as a powerhouse in open-source AI, delivering top-tier multilingual performance, efficient MoE scaling, and strong reasoning/agent capabilities that rival proprietary leaders. With over 700 million downloads and full Apache 2.0 openness, it’s incredibly accessible for developers and global users. Free chat plus affordable API make it a go-to for productivity, coding, and research.

FAQs

  • What is Qwen3?

    Qwen3 is Alibaba’s advanced open-source large language model family released in April 2025, featuring dense and MoE variants with superior multilingual capabilities, reasoning, and agentic performance across 119 languages.

  • When was Qwen3 released?

    The core Qwen3 family launched on April 28, 2025, with subsequent variants like Qwen3-Max in September 2025 and specialized models in 2026.

  • How many downloads does Qwen have?

    The Qwen family surpassed 700 million cumulative downloads on Hugging Face by January 2026, leading global open-source AI adoption.

  • Is Qwen3 free to use?

    Yes, most models are fully open-source under Apache 2.0 for free download and local use; chat.qwen.ai is free with limits; API is token-based paid.

  • What are the main strengths of Qwen3?

    Excels in multilingual tasks (119 languages), reasoning, coding, math, agent capabilities, and efficient MoE scaling for high performance at lower cost.

  • How can I access Qwen3?

    Use free chat at chat.qwen.ai, download weights from Hugging Face/ModelScope, or integrate via Alibaba Cloud API or third-party providers like Groq.

  • Does Qwen3 support reasoning modes?

    Yes, it features hybrid thinking/non-thinking modes (toggle via tokenizer or prompt) for balancing speed and depth in complex tasks.

  • What context window does Qwen3 have?

    Up to 128K tokens in most variants (extended further in some like Qwen3-Max), enabling long-document and multi-turn processing.

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