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Local LLM Guide

Model

Qwen3.5 9B

Start with a supported compressed build and short context. 32GB RAM estimate. Best use: General-purpose local Qwen on 16GB or 32GB systems.

9BMultimodal

Best use

General-purpose local Qwen on 16GB or 32GB systems.

Memory planning

32GB RAM estimate

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?

  • General-purpose local Qwen on 16GB or 32GB systems.

Choose something else when

  • You only have 8GB RAM or need very fast responses.

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
Use a smaller model for this memory limit.
16GB system memory
Memory or response time may limit use. Try a smaller model first.
32GB system memory
A possible starting point with a compressed model and short conversation; check the exact file size.
8GB GPU memory
Use a smaller model for this memory limit.
12GB GPU memory
Use a smaller model for this memory limit.
24GB GPU memory
Memory or response time may limit use. Try a smaller model first.
Apple unified memory
Memory or response time may limit use. Try a smaller model first.

Model facts that change the decision

Parameters
9B
Input
Text · Image
Published context limit
262,144 tokens
Model format
safetensors · GGUF · Ollama · MLX
Suggested compression
Q4_K_M for first local attempts unless a cited runtime recommends a different default.
Typical Q4 file
6.6GB 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 qwen3.5:9b

LM Studio: Check that your installed app supports the exact model format and task before downloading it.

llama.cpp

Use a cited GGUF build with current llama.cpp-compatible tooling.

Conditions that change the answer

  • Q4 is the practical beginner quantization; Q8 needs more memory headroom.
  • The 256K context limit is theoretical for many local setups.
  • Vision and thinking mode increase latency and memory use.
  • Commercial use: permitted
  • The best beginner default in the Qwen3.5 line: still laptop-realistic, but more capable than the 4B model for multilingual chat, reasoning, coding help, and image-aware local workflows.

Read the controlling license text →