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Text model · Qwen3-VL

Qwen3-VL 30B-A3B: RAM and VRAM requirements

Qwen3-VL 30B-A3B needs about 20.4 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~18.29 GB to download; KV cache and overhead add the rest), or about 33.4 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 4090 (24GB).

Qwen3-VL family · 31.1B params (Mixture-of-Experts: activates only 3B of 31.1B params per token, so generation is faster than the total size suggests) · released Oct 2025.

Shopping for hardware? See what runs Qwen3-VL 30B-A3B →

Vision · accepts images License Apache-2.0 · Commercial OK ↓ 416.1K/mo ♥ 610 on HuggingFace
Q4_K_M GGUF
18.29 GB
Q8_0 GGUF
31.26 GB
Memory @ Q4 (4k)
~20.4 GB
Context
256 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?

Qwen3-VL 30B-A3B runs on 13 of 43 tracked devices at Q4_K_M.

12 run well 1 tight fit 30 too small
Fit check Q4_K_M
No, not enough memory
needs 20.4 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)18.29 GB
+
KV cache (4k)1.3 GB
+
Overhead0.8 GB
=
Total20.4 GB

How context length changes it

4k context ~20.4 GB 32k context ~29.8 GB 128k context ~61.9 GB

Longer context grows the KV cache, which for Qwen3-VL 30B-A3B is sized by its 3B active params, not the full 31.1B. It needs ~20.4 GB at 4k and ~61.9 GB at 128k.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 13 GB est
Q3_K_M 15.2 GB est
Q4_K_M (default) 18.29 GB
Q5_K_M 22.2 GB est
Q6_K 25.5 GB est
Q8_0 31.26 GB
FP16 62.2 GB est

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

Run it

Ollama
$ ollama run qwen3-vl:30b
llama.cpp
$ llama-cli -hf Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF:Q4_K_M
LM Studio
$ lms get Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF

Which devices can run Qwen3-VL 30B-A3B?

NVIDIA GPUs

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

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 North Mini Code 1.0 30.5B Next size up Qwen2.5 32B 32B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does Qwen3-VL 30B-A3B need?

At Q4_K_M, Qwen3-VL 30B-A3B needs about 20.4 GB (weights ~18.29 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~33.4 GB.

What is the Q4_K_M GGUF file size of Qwen3-VL 30B-A3B?

The Q4_K_M GGUF file is about 18.29 GB to download, and the Q8_0 GGUF is about 31.26 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~20.4 GB of memory at Q4_K_M.

Can Qwen3-VL 30B-A3B run on a laptop?

Qwen3-VL 30B-A3B is large; you need a 24 GB+ GPU or a 32-48 GB Mac at Q4_K_M.

Is Qwen3-VL 30B-A3B cheaper to run because it is a MoE model?

It is faster, not lighter. Qwen3-VL 30B-A3B activates only 3B of 31.1B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 31.1B.

Can I use Qwen3-VL 30B-A3B commercially?

Yes. Qwen3-VL 30B-A3B is licensed Apache-2.0, which permits commercial use.

Understand the numbers

Short guides to the ideas behind Qwen3-VL 30B-A3B's memory and quant figures.

Official Qwen GGUF files measure Q4_K_M at 18,556,687,168 bytes and Q8_0 at 32,483,932,992 bytes. The 1,083,499,584-byte F16 mmproj is folded into the 18.29GB and 31.26GB totals. Ollama qwen3-vl:30b defaults to Q4_K_M and pulls 19,595,386,752 bytes independently. A3B denotes 3B activated parameters per token. Vision input needs an mmproj-capable runtime.

Sources

Catalog updated 2026-10-05. Memory figures are estimates. See methodology.