LocalClaw/LLM/Qwen 3 Next (80B/3B MoE)
Open-weight local LLM

Qwen 3 Next (80B/3B MoE)

Alibaba's next-gen MoE with hybrid-gated DeltaNet attention. Only 3B active params — runs at dense 7B speed with 70B quality. 256K native context (extensible to 1M). Hybrid thinking mode. Apache 2.0.

64 GB workstation 64 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
80B (3B active)
Minimum RAM
64 GB
Model size
48 GB
Quantization
Q4_K_M

Can Qwen 3 Next (80B/3B MoE) run locally?

Qwen 3 Next (80B/3B MoE) is best for 64 GB workstations and larger Apple Silicon or NVIDIA setups.

Search for qwen3-next-80b-a3b in LM Studio or another GGUF-compatible runtime.

Qwen/Qwen3-Next-80B-A3B-Instruct
chatcodereasoningpowerquality

Install path

01
Check RAM fitMinimum 64 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch qwen3-next-80b-a3b in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Alibaba's next-gen MoE with hybrid-gated DeltaNet attention. Only 3B active params — runs at dense 7B speed with 70B quality. 256K native context (extensible to 1M). Hybrid thinking mode. Apache 2.0.

Limitations

  • Performance depends on quantization, RAM bandwidth and runtime support.

Best use cases

  • chat
  • code
  • reasoning
  • power
  • quality

Capability profile

speed
8
quality
9
coding
9
reasoning
9

Technical notes

Developer
qwen-moe
License
See model repository
Context window
Unknown tokens
Architecture
See model card

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.

Workstation fitMac Studio M4 Max 64GBCUDA workstation classNVIDIA GB10 / DGX SparkLarge local models64GB RAM guide

Where to go next