LocalClaw/LLM/Qwen AgentWorld 35B-A3B
Open-weight MoE

Qwen AgentWorld 35B-A3B

Catalogue summary: Official Qwen language world model for simulating agent environments across terminal, web, OS, Android, search, SWE and tool-calling domains. Apache 2.0 with active GGUF and MLX quantizations.

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

32 GB catalogue minimum32 GB RAMQ4_K_MCoding assistant
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Parameters
35B (3B active, MoE)
Minimum RAM
32 GB
Model size
20 GB
Quantization
Q4_K_M

Can Qwen AgentWorld 35B-A3B run locally?

Qwen AgentWorld 35B-A3B has a catalogue minimum of 32 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use qwen-agentworld-35b-a3b as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

Model sourcePublic GGUF repository (verified 2026-09-07): unsloth/Qwen-AgentWorld-35B-A3B-GGUFUpstream releasePaper or model cardLicence text
chatcodereasoningagentpower

Install path

01
Check RAM fitMinimum 32 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch qwen-agentworld-35b-a3b in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: qwen
  • Parameters: 35B (3B active, MoE)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 32 GB
  • Catalogue model size: 20 GB
  • Tags: chat, code, reasoning, agent, 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

  • chat
  • code
  • reasoning
  • agent
  • power

Capability profile

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

speed
5
quality
8
coding
8
reasoning
9

Technical notes

Developer
Alibaba Cloud (Qwen Team)
License
Apache 2.0
Context window
262,144 tokens
Architecture
Qwen3.5 MoE-based language world model with 35B total parameters, about 3B active parameters, Gated DeltaNet, gated attention, 256 experts and 8 routed experts plus one shared expert per token.

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.

Comfortable headroomMac mini M4 Pro 48GBMobile workstationMacBook Pro M4 Max 36GBPower-user picks32GB RAM guide

Related catalogue entries

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

Qwen 3 (32B) 32BQwen 3.5 (27B) 27BQwen 3.6 (27B) 27BQwen 3.6 35B-A3B 35B (3B active, MoE)Qwen3.8-27B 27BQwen 3.5 MoE (35B/3B active) 35B (3B active)Qwen 3 (14B) 14BQwen 3.5 MoE (122B/10B active) 122B (10B active)

Where to go next