Qwen2.5-3B-Instruct
Qwenothertext

Qwen2.5-3B-Instruct

Updated Aug 24, 2026
Parameters
3.1B
Context
32,768
License
other
Updated
Aug 24, 2026

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at FP16
4 of 4 quantizations fit Qwen2.5-3B-Instruct with real runtime overhead.
Q4_K_M
2 GB
Q5_K_M
2 GB
Q8_0
3 GB
FP16
6 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve Qwen/Qwen2.5-3B-Instruct

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

Qwen2.5-3B-Instruct is a 3.1B-parameter other model from Qwen. At Q4_K_M it needs roughly 2 GB of VRAM, placing it in the CPU / ≤4 GB hardware tier.

Popularity

Qwen2.5-3B-Instruct has 7,534,511 downloads in the last month on HuggingFace and 552 likes.

Frequently asked

Quick answers to common questions

How much VRAM does Qwen2.5-3B-Instruct need?

Qwen2.5-3B-Instruct with 3.1B parameters needs approximately 2 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Qwen2.5-3B-Instruct better than other Qwen models?

Qwen2.5-3B-Instruct has 3.1B parameters with 32,768 context - a strong choice for general use.

What license is Qwen2.5-3B-Instruct under?

Qwen2.5-3B-Instruct is released under the other license, making it suitable for most commercial and personal projects.

What hardware runs Qwen2.5-3B-Instruct well?

With 3.1B parameters, Qwen2.5-3B-Instruct requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for Qwen2.5-3B-Instruct?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~2 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can Qwen2.5-3B-Instruct's context window handle?

Qwen2.5-3B-Instruct supports a 32,768-token context window - enough for most medium-length documents and conversations. Real-world usable context may vary by implementation.

What models compete with Qwen2.5-3B-Instruct?

Qwen2.5-3B-Instruct competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec

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