Qwen2.5 is Alibaba’s latest open-source model family and one of the most capable models available in Ollama. It punches well above its weight at smaller sizes, making it a popular choice for anyone running local AI on modest hardware. This guide walks you through getting it running and what it’s actually good at.
What is Qwen2.5?
Qwen2.5 is the second major generation of Alibaba’s Qwen model series, released in late 2024. It comes in multiple sizes — from 0.5B all the way up to 72B parameters — and includes specialist variants trained specifically for coding (Qwen2.5-Coder) and mathematics (Qwen2.5-Math).
The standout feature of Qwen2.5 is its performance at smaller sizes. The 7B and 14B models consistently outperform equivalently-sized Llama models on most benchmarks, making it a good choice if you have limited VRAM or RAM.
Qwen2.5 Model Sizes Available in Ollama
| Model | RAM needed | Best for |
|---|---|---|
| qwen2.5:0.5b | ~1 GB | Very low-end hardware, simple tasks |
| qwen2.5:1.5b | ~2 GB | Basic Q&A, lightweight tasks |
| qwen2.5:3b | ~3 GB | Good balance on older hardware |
| qwen2.5:7b | ~6 GB | Most users — excellent quality/speed balance |
| qwen2.5:14b | ~10 GB | High quality, needs 16 GB RAM minimum |
| qwen2.5:32b | ~22 GB | Near-frontier quality, needs 32 GB RAM |
| qwen2.5:72b | ~48 GB | Best quality, workstation/server only |
How to Install Qwen2.5 in Ollama
Make sure Ollama is installed first, then open a terminal and run:
ollama pull qwen2.5This downloads the default 7B model. To pull a specific size:
ollama pull qwen2.5:14bFor the coding specialist variant:
ollama pull qwen2.5-coder:7bHow to Run Qwen2.5
To start an interactive chat session:
ollama run qwen2.5Or to run a specific size:
ollama run qwen2.5:14bType your message and press Enter. Type /bye to exit.
What is Qwen2.5 Good At?
Qwen2.5 is a strong all-rounder, but particularly good at:
- Multilingual tasks — excellent support for Chinese, Japanese, Korean and European languages alongside English
- Long context — supports up to 128K token context window, useful for processing long documents
- Instruction following — very good at following structured prompts and multi-step instructions
- Coding — the Qwen2.5-Coder variants are among the best small coding models available locally
- Structured output — reliable JSON generation and function calling support
Qwen2.5 vs Llama 3.1 — Which Should You Use?
For most tasks on modest hardware, Qwen2.5 7B and 14B are worth trying before Llama 3.1 equivalents — they tend to produce more detailed, structured responses. However, Llama 3.1 has a larger community and more fine-tuned variants available. Try both and see which suits your use case.
Qwen2.5-Coder: The Specialist Variant
If you’re primarily using Ollama for coding assistance, Qwen2.5-Coder is worth pulling separately:
ollama pull qwen2.5-coder:7bIt supports over 40 programming languages and was specifically trained on code data. At 7B parameters it runs comfortably on 8 GB of RAM and outperforms the base model on most coding tasks.
Tips for Getting the Best Results
- Start with the 7B model — it’s the best balance of quality and speed for most users
- Use a system prompt to set context and tone for longer conversations
- For coding tasks, always use Qwen2.5-Coder rather than the base model
- If responses are slow, check whether Ollama is using your GPU — see our guide: Ollama GPU Not Detected Fix
