LocalClaw/LLM/MiroThinker 1.7 (30B MoE)
Open-weight MoE

MiroThinker 1.7 (30B MoE)

MiroMind AI second-gen deep-research agent. 30B MoE with stronger tool-use, 256K context, SOTA on BrowseComp-ZH (Chinese research). Designed for agentic workflows, not casual chat. Released March 2026. Apache 2.0.

64 GB workstation 48 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
30B (3B active, MoE)
Minimum RAM
48 GB
Model size
18 GB
Quantization
Q4_K_M

Can MiroThinker 1.7 (30B MoE) run locally?

MiroThinker 1.7 (30B MoE) is best for 64 GB workstations and larger Apple Silicon or NVIDIA setups.

Search for mirothinker-1.7 in LM Studio or another GGUF-compatible runtime.

miromind-ai/MiroThinker-1.7
reasoningcodepowerquality

Install path

01
Check RAM fitMinimum 48 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch mirothinker-1.7 in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • MiroMind AI second-gen deep-research agent. 30B MoE with stronger tool-use, 256K context, SOTA on BrowseComp-ZH (Chinese research). Designed for agentic workflows, not casual chat. Released March 2026. Apache 2.0.

Limitations

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

Best use cases

  • reasoning
  • code
  • power
  • quality

Capability profile

speed
3
quality
9
coding
8
reasoning
10

Technical notes

Developer
mirothinker
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