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Text model · Qwen2.5-VL

Qwen2.5-VL 3B: RAM and VRAM requirements

Qwen2.5-VL 3B needs about 4.4 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~3.05 GB to download; KV cache and overhead add the rest), or about 6.4 GB at Q8_0. The lightest hardware that runs it is Apple M1 (8GB).

Qwen2.5-VL family · 3.75B params · released Jan 2025.

Shopping for hardware? See what runs Qwen2.5-VL 3B →

Vision · accepts images License Apache-2.0 · Commercial OK ↓ 8.2M/mo ♥ 681 on HuggingFace
Q4_K_M GGUF
3.05 GB
Q8_0 GGUF
5.1 GB
Memory @ Q4 (4k)
~4.4 GB
Context
32 k

Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.

Will it run on your device?

Qwen2.5-VL 3B runs on 40 of 40 tracked devices at Q4_K_M.

34 run well 6 tight fit 0 too small
Fit check Q4_K_M
Yes, it runs fast
needs 4.4 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)3.05 GB
+
KV cache (4k)0.5 GB
+
Overhead0.8 GB
=
Total4.4 GB

How context length changes it

4k context ~4.4 GB 32k context ~7.6 GB 128k context ~18.8 GB

Qwen2.5-VL 3B is small enough that the context window is the thing to size for: 128k needs ~18.8 GB versus ~4.4 GB at 4k, so pick the window you actually use.

Speed drops too: every token re-reads the KV cache, so at 128k context Qwen2.5-VL 3B generates at roughly ~17% of its short-context speed. How this is estimated.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 1.6 GB est
Q3_K_M 1.8 GB est
Q4_K_M (default) 3.05 GB
Q5_K_M 2.7 GB est
Q6_K 3.1 GB est
Q8_0 5.1 GB
FP16 7.5 GB est

Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.

Run it

llama.cpp
$ llama-cli -hf ggml-org/Qwen2.5-VL-3B-Instruct-GGUF:Q4_K_M
LM Studio
$ lms get ggml-org/Qwen2.5-VL-3B-Instruct-GGUF

Which devices can run Qwen2.5-VL 3B?

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

NVIDIA GPUs

AMD GPUs

Same job, different size

Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.

Next size down Granite 4.1 3B 3.4B Next size up Phi-4-mini 3.8B 3.8B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does Qwen2.5-VL 3B need?

At Q4_K_M, Qwen2.5-VL 3B needs about 4.4 GB (weights ~3.05 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~6.4 GB.

What is the Q4_K_M GGUF file size of Qwen2.5-VL 3B?

The Q4_K_M GGUF file is about 3.05 GB to download, and the Q8_0 GGUF is about 5.1 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~4.4 GB of memory at Q4_K_M.

Can Qwen2.5-VL 3B run on a laptop?

Yes, Qwen2.5-VL 3B fits on a 16 GB machine at Q4_K_M and runs on Apple Silicon or a 12 GB+ GPU comfortably.

Can I use Qwen2.5-VL 3B commercially?

Yes. Qwen2.5-VL 3B is licensed Apache-2.0, which permits commercial use.

Understand the numbers

Short guides to the ideas behind Qwen2.5-VL 3B's memory and quant figures.

Qwen2.5-VL 3B vision-language model: chats about images. Q4_K_M ~1.8GB plus a ~1.25GB fp16 vision projector (mmproj), folded into the totals. Sizes from the ggml-org GGUF repo. Vision input needs an mmproj-capable runtime (llama.cpp, LM Studio); many mobile runtimes do not support it yet.

Sources

Last validated 2026-08-03. Memory figures are estimates. See methodology.