Qwen 3

Heard the buzz about Artificial Intelligence (AI) like ChatGPT? Get ready for another leap forward! Tech giant Alibaba Cloud released Qwen 3 in late April 2025. It’s a brand new, incredibly smart AI family – specifically, a type of AI called a Large Language Model (LLM) – that you can actually use yourself. The best part? It’s completely free and open-source, meaning free for almost anyone to download, use, and even build upon!


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qwen 3
Table of Contents

What Makes Qwen 3 Special? (Explained Simply)

Let’s recap what makes Qwen 3 stand out:

Models for Everyone (Size & Type):

  • Qwen 3 comes in sizes from 0.6B to a massive 235B. The ‘B’ means Billions of parameters (think tiny dials storing knowledge) – more ‘B’ usually means smarter AI but needs more computer power (VRAM). It includes standard ‘Dense’ models (all parts always active) and efficient ‘MoE’ models (like a team of specialists, only activating needed parts, giving big-model smarts with less active computation).

Smart “Hybrid Thinking”:

  • Its unique ‘Hybrid Thinking’ lets it give fast, direct answers or choose to ‘think step-by-step’ (sometimes showing its work in <think> tags) for complex problems, boosting accuracy when needed.

Huge Memory (Long Context):

  • It remembers long conversations! Qwen 3 handles huge ‘context windows’ (up to 128,000 ‘tokens’ or word pieces for larger models), letting it process entire books or codebases without forgetting the start.

Speaks Many Languages:

  • Trained on 119 languages, it’s great for translation and global communication.

Truly Free & Open (Apache 2.0):

  • This open-source license means it’s free to use, modify, and even use commercially. You control your data and aren’t locked into a paid service. (Link: Apache 2.0 License Details)

Very Efficient:

  • Smaller Qwen 3 models perform like much bigger older ones – more power on less demanding hardware!

what makes qwen 3 special

Qwen 3 Benchmarks: How Does It Compete?

qwen 3 benchmarks
Okay, let’s talk performance. How does Qwen 3 stack up against well-known models based on common AI tests (benchmarks)? Here’s what the reports and official announcements suggest:

Qwen 3 vs ChatGPT vs Gemini vs Deepseek

  • Qwen3-235B-A22B (The Flagship): Alibaba positions this model as highly competitive against other elite models.
    • vs. Gemini 2.5 Pro: Reports indicate Qwen3-235B achieves performance parity with Gemini 2.5 Pro on several benchmarks.
    • vs. OpenAI o1/o3-mini: On tough math reasoning tests like AIME, Qwen3-235B reportedly outperforms these older (but still strong) OpenAI reasoning models. It also shows an edge over o3-mini in coding benchmarks like LiveCodeBench. (Note: It might slightly trail the absolute newest OpenAI models on some specific tests, but it’s clearly competitive.)
    • vs. DeepSeek R1: Qwen3-235B is presented as competitive with or potentially exceeding DeepSeek R1 on various capability, math, and coding benchmarks. It also reportedly surpasses DeepSeek R1 on the Arena-Hard benchmark (measuring human preference) and the BFCL benchmark (evaluating tool/agent abilities).
  • Qwen3-30B-A3B (Efficient MoE): This model demonstrates the power of MoE.
    • It’s claimed to significantly outperform QwQ-32B (a previous strong reasoning model from Qwen) despite using only about 1/10th the active parameters.
    • Some reports suggest it challenges models like DeepSeek-V3 on certain benchmarks, showcasing impressive capability for its active size.
  • Smaller Dense Models (e.g., Qwen3-4B, Qwen3-32B):
    • These show remarkable efficiency gains. Qwen3-4B is often compared to the much larger Qwen2.5-72B, offering similar performance. The Qwen3-32B model is claimed to surpass the performance of the previous generation Qwen2.5-72B.

Key Takeaway on Performance:

Qwen 3, especially its larger models, operates at the cutting edge of AI capabilities, particularly excelling in reasoning, math, and coding tasks according to published benchmarks. It stands as a strong competitor to models from Google (Gemini), OpenAI (its reasoning series), and other leading open-source players like DeepSeek. While the absolute newest proprietary models might hold a slight edge in some areas, Qwen 3 significantly closes the gap.

And remember, Qwen 3 achieves this high performance while being fully open-source under the Apache 2.0 license – a massive advantage in terms of freedom, cost, and privacy!

What Cool Things Can Qwen 3 Do?

If you want to see the experiments we have done with Qwen 3 check this post

  • Summarize Anything: Long articles, boring reports? Ask Qwen 3 for the key points (bigger models handle longer texts better).
  • Be a Better Writer: Stuck? Ask for ideas, help drafting emails, rephrase awkward sentences, check grammar in many languages!
  • Learn Languages: Practice conversations, ask for translations, get grammar explained simply.
  • Code Smarter: Get coding examples, ask it to explain confusing code, find bugs, write simple scripts (larger models are better coders).
  • Solve Problems: Tackle tricky questions, work through logic puzzles, explain scientific concepts (Thinking Mode helps!).

Where Can You Use or Try Qwen 3? (Other Options)

Official Qwen Chat (Easiest Way to Try)

  • Alibaba provides a web interface and mobile app for direct chatting. Ideal for quick tests without any setup.
  • Try it here: chat.qwen.ai (Note: Availability/login requirements may vary by region)

LM Studio (Popular Local GUI)

  • A user-friendly desktop application for running local AI models. Supports the common GGUF quantized format often used for Qwen 3. Good if you prefer a graphical interface.
  • Note: Check LM Studio’s model compatibility list for the latest Qwen 3 support status.

Llama.cpp (Advanced Local Use)

  • A powerful C++ library for efficiently running quantized GGUF models. Offers maximum control for technical users but requires command-line use and more setup.

Hugging Face (For Developers & Downloading Models)

Cloud APIs (For Scalable Developer Use)

  • Developers needing scalable access without managing hardware can use APIs. Alibaba provides this via DashScope / Model Studio. Third-party cloud platforms may also offer Qwen 3. (Usually involves usage-based costs).

Can Your Computer Run Qwen 3? (Hardware Guide)

can my computer run qwen 3
Running AI locally needs specific computer resources, mainly your Graphics Card’s (GPU’s) dedicated memory, called VRAM.

VRAM and Quantization Explained Briefly

  • VRAM: This is your graphics card’s dedicated memory, like its personal workbench. AI models need to fit in VRAM to run fast. More VRAM = bigger workbench = can run bigger, smarter AI.
  • Quantization: This is a clever trick (like making a map smaller but still useful) that shrinks the AI model’s file size so it uses much less VRAM. Common quantized files (like GGUF Q4_K_M) let you run powerful models on less powerful hardware with only a tiny quality difference. Always try a quantized version first!

Hardware Needs vs. Qwen 3 Models:

  • Basic PCs/Laptops (~4-8GB VRAM): Can try the smallest models (0.6B, 1.7B). Might be slow, especially without a dedicated GPU (running on the main CPU). Good for basic chat/tasks.
  • Decent Gaming PCs/Modern Laptops (~8-16GB VRAM): Ideal for medium models (4B, 8B). Great all-around helpers for coding, writing, translation. Needs a modern GPU. 12GB+ VRAM is better for 8B.
  • High-End PCs/Workstations (16-24GB+ VRAM): Needed for larger models (14B, 32B, 30B MoE). For high-quality results in complex tasks. Requires powerful GPUs.
  • Data Centers: Required for the biggest model (235B MoE). Not for home use.

Run Qwen 3 Locally with Ollama

Ollama makes trying powerful AI surprisingly simple. It handles the complicated setup stuff for you. Here’s the detailed step-by-step guide:

Step 1: Install Ollama

  • Go to ollama.com, download the installer for your operating system (Windows, Mac, or Linux), and run the installation process. Simple!

Step 2: Download & Run Qwen 3 via Command Line

  • Open your computer’s command line tool (Terminal on Mac/Linux, Command Prompt or PowerShell on Windows).
  • Choose a quantized model size suitable for your PC (check the hardware guide above!). The 8B Q4_K_M quant is often a good starting point, offering a great balance: 
    ollama run qwen3:8b-q4_K_M
    • (Tip: You can adjust the tag based on your hardware: qwen3:4b-q4_K_M needs less VRAM, qwen3:14b-q4_K_M needs more. Using just qwen3:8b usually lets Ollama pick a default quantized version.)
  • The first time you run this, Ollama will download the model file. This can take a while as the files are large (several Gigabytes!). Be patient.

Step 3: Chat!

  • Once the download is complete and the model loads, you’ll see a prompt like >>> Send a message (/? for help):. Now you can start chatting! Type your question or instruction and press Enter.
  • >>> How does photosynthesis work? Explain it simply.

Step 4: Stop the AI

  • When finished chatting, type /bye and press Enter to exit and unload the model.

Which Qwen 3 Model Size is Right for Your Use Case?

Picking the right size affects what you can realistically do:

which qwen 3 model size is right for me

Qwen3-0.6B, 1.7B (Small):

  • Best For: Learning AI basics, simple chatbots, extracting keywords, running on very low-power devices.

Qwen3-4B, 8B (Medium):

  • Best For: Most home users! General assistance, coding help, solid translation, creative writing drafts, summarizing documents. Runs well on typical gaming PCs/modern laptops.

Qwen3-14B, 32B, 30B MoE (Large):

  • Best For: Users needing high quality: complex coding, advanced math/logic problems (use Thinking Mode!), professional writing, building AI agents. Requires powerful GPUs.

Qwen3-235B MoE (Massive):

  • Best For: Companies and researchers needing top-tier AI for huge tasks, scientific discovery, enterprise solutions. Requires data center hardware.

Conclusion: Your AI Adventure Starts Now!

Qwen 3 is a huge step forward, bringing top-tier AI power to everyone, for free. It’s smart, flexible, speaks many languages, remembers long conversations, and puts you in control thanks to its open-source nature.

With easy tools like Ollama making installation simple, there’s never been a better time to explore advanced AI on your own computer. Pick a model size that fits your hardware, follow the simple steps, tweak the settings, and discover what you can achieve.