Open-weight local LLM

QwQ (32B)

Catalogue summary: Early Qwen reasoning model. Superseded by GLM-4 32B and Qwen 3 32B for most tasks. Still decent for pure math.

Repository editorial metadata; verify comparative claims in the linked upstream material.

24 GB catalogue minimum24 GB RAMQ4_K_MReasoning
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Parameters
32B
Minimum RAM
24 GB
Model size
19 GB
Quantization
Q4_K_M

Can QwQ (32B) run locally?

QwQ (32B) has a catalogue minimum of 24 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use qwq-32b-preview as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

reasoningpower

Install path

01
Check RAM fitMinimum 24 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch qwq-32b-preview in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: qwen
  • Parameters: 32B
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 24 GB
  • Catalogue model size: 19 GB
  • Tags: reasoning, power

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Catalogue tags

  • reasoning
  • power

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

speed
4
quality
7
coding
6
reasoning
8

Technical notes

Developer
Alibaba Cloud (Qwen Team)
License
Apache 2.0
Context window
131,072 tokens
Architecture
Reasoning-focused Transformer

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

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