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Local LLM Guide

Model

Qwen3-VL 235B-A22B Instruct

Start with a supported compressed build and short context. Memory requirement not supplied; check the model and app instructions. Best use: Server GPUs, cloud deployment, maximum visual reasoning, long documents, video, and demanding agent workflows production.

235B total / 22B activeVision language

Best use

Server GPUs, cloud deployment, maximum visual reasoning, long documents, video, and demanding agent workflows production.

Memory planning

Memory requirement not supplied; check the model and app instructions

Expected pace

Depends on your hardware, app, and conversation length

License

Apache-2.0; read the model’s terms before use

Who should use this model?

  • Server GPUs, cloud deployment, maximum visual reasoning, long documents, video, and demanding agent workflows production.

Choose something else when

  • Avoid if you are a beginner, use consumer hardware, or expect simple local installation today.

What hardware makes sense?

The download is only part of the memory needed. Leave room for the app, the input it processes, and other open programs. For chat models, context includes the instructions, conversation, and answer. Longer context needs more memory.

CPU only
Use a smaller model for this memory limit.
8GB system memory
Check this model with your exact hardware and settings before choosing it.
16GB system memory
Check this model with your exact hardware and settings before choosing it.
32GB system memory
Check this model with your exact hardware and settings before choosing it.
8GB GPU memory
Check this model with your exact hardware and settings before choosing it.
12GB GPU memory
Check this model with your exact hardware and settings before choosing it.
24GB GPU memory
Check this model with your exact hardware and settings before choosing it.
Apple unified memory
Check this model with your exact hardware and settings before choosing it.

Model facts that change the decision

Parameters
235B total / 22B active
Input
Text input · Image input · Multi image input · Video input in supported runtimes · Text output
Published context limit
262,144 tokens
Model format
safetensors · GGUF · Ollama
Suggested compression
Q4_K_M for first local attempts unless a cited runtime recommends a different default.
Typical Q4 file
142GB before runtime and context overhead
Languages
Unknown

Using image input

This model needs an app or library that supports its image-processing components. Follow the exact model’s instructions for preparing image inputs. Some GGUF downloads also need a matching projector file; loading the text model alone does not establish image support.

First setup

Ollama

ollama run qwen3-vl:235b

llama.cpp

Use the cited GGUF repository (Qwen/Qwen3-VL-235B-A22B-Instruct-GGUF) with current llama.cpp-compatible tooling.

Conditions that change the answer

  • Use server hardware for this model.
  • Ollama also lists cloud tags for 235B; local Q4_K_M GGUF is still about 142GB before runtime overhead.
  • GGUF sizes are for Q4_K_M and Q8_0; a Q5 size was not found in the cited sources.
  • The minimum memory is not specified here. Check the full model size, app requirements, and conversation memory before choosing hardware.
  • Commercial use: Permitted under Apache-2.0 license, subject to license terms.
  • Qwen3-VL 235B-A22B is a server-class flagship, not a normal local recommendation. It belongs in the catalog for labs, cloud users, and teams needing maximum Qwen3-VL quality over convenience, speed, or hardware simplicity in production deployments.

Read the controlling license text →