Open-weight MoE
DeepSeek V3.1 (671B MoE)
Hybrid thinking/non-thinking model. Full 671B MoE for maximum quality, 37B active at inference. Significant step up from V3.0. Requires server-grade hardware. MIT licensed.
Server-grade
512 GB RAM
Q4_K_M
Maximum quality outputs
Parameters
671B (37B active, MoE)
Minimum RAM
512 GB
Model size
360 GB
Quantization
Q4_K_M
Can DeepSeek V3.1 (671B MoE) run locally?
DeepSeek V3.1 (671B MoE) is server-grade locally. Keep it for comparison unless you have very large unified memory, multiple GPUs or remote inference.
Search for deepseek-v3.1 in LM Studio or another GGUF-compatible runtime.
unsloth/DeepSeek-V3.1-GGUFchatreasoningquality
Install path
01
Check RAM fitMinimum 512 GB RAM. Start with the Q4_K_M quant.02
Load the modelSearch deepseek-v3.1 in LM Studio.03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.Strengths
- Hybrid thinking/non-thinking mode
- Only 37B active parameters despite 671B total
- Top-tier quality
- Among best open models ever
Limitations
- Requires 512GB+ RAM for full model
- Server-grade hardware only
- Complex setup
Best use cases
- Maximum quality outputs
- Research
- Enterprise deployment
- Frontier AI tasks
Capability profile
Technical notes
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.