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!

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)

Besides Ollama, here are other ways to access Qwen 3:

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.