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97Safety, Privacy & Open ModelsFreeAge: Any

Qwen (Alibaba)

qwen.ai

Best for

Multilingual AI with strong Chinese/English performance

Works on

Local (via Ollama) or API

Alternatives

LLaMA, Mistral

Watch out

Alibaba-developed; check data governance for your context

What It Does

Qwen is Alibaba Cloud's open-weight model family, with versions ranging from 0.5B to 110B parameters. Qwen 2.5 models are multilingual (particularly strong in Chinese, English, and several Indian languages), support 128K context windows, and include specialised variants for coding (Qwen-Coder), mathematics (Qwen-Math), and vision (Qwen-VL). In several independent benchmarks, Qwen 2.5 72B matches or exceeds LLaMA 3.1 70B and Mistral Large. Its small models (0.5B–7B) are designed to run on phones and edge devices.

Setup in 5 Minutes

. - Choose the parameter size that fits your hardware (7B for laptops, 32B for desktops with a good GPU, 72B for workstations). - For the API, use Alibaba's DashScope or access Qwen on Hugging Face. - The model weights are released under the Apache 2.0 licence, which is more permissive than Meta's LLaMA licence for commercial use.

Try This

Run Qwen 2.5 7B locally and test its multilingual ability: give it a paragraph in English and ask it to translate into Hindi, then summarise the Hindi text in English. Compare with the same task on LLaMA and Mistral. Then test Qwen-Coder on a programming task—ask it to write a Python function, explain the code, and generate unit tests. Evaluate which model gives the best code quality at the 7B size.

Follow Along

Follow Along — Multilingual Translation Test: - Take the Hindi output and prompt: "Translate this Hindi text into Tamil." - Take the Tamil output and prompt: "Translate this Tamil text back into English." - Compare the final English version with your original. Highlight every factual drift, lost nuance, or altered number. This reveals where multilingual AI translation breaks down.

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