LocalClaw/LLM/Ling 1T (1T MoE)
Open-weight local LLM

Ling 1T (1T MoE)

Ant Group / InclusionAI trillion-param MoE. 50B active per token, 128K context. Strong Chinese + English, open weights with commercial licence. Tops many bilingual benchmarks. Datacenter-only.

Server-grade 1024 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
1T (50B active)
Minimum RAM
1024 GB
Model size
620 GB
Quantization
Q4_K_M

Can Ling 1T (1T MoE) run locally?

Ling 1T (1T MoE) is server-grade locally. Keep it for comparison unless you have very large unified memory, multiple GPUs or remote inference.

Search for ling-1t in LM Studio or another GGUF-compatible runtime.

inclusionAI/Ling-1T
chatcodereasoningquality

Install path

01
Check RAM fitMinimum 1024 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch ling-1t in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Ant Group / InclusionAI trillion-param MoE. 50B active per token, 128K context. Strong Chinese + English, open weights with commercial licence. Tops many bilingual benchmarks. Datacenter-only.

Limitations

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

Best use cases

  • chat
  • code
  • reasoning
  • quality

Capability profile

speed
2
quality
10
coding
9
reasoning
9

Technical notes

Developer
ling
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.

Very large memoryMac Studio Ultra classCheck model size firstNVIDIA GB10 / server optionsMore practical alternativesCompare smaller models

Where to go next