LocalClaw/LLM/DeepSeek V3.1 (671B MoE)
Open-weight MoE

DeepSeek V3.1 (671B MoE)

Catalogue summary: 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.

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

512 GB catalogue minimum512 GB RAMQ4_K_MReasoning
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This is an advanced workstation/server GGUF path. Unsupported apps are clearly marked.

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Open on Hugging FaceFiles, licence and available downloadsOpen llama.cpp setupAdvanced option: opens GGUF files and patch notesUse with LocalClawOptional workspace after the model is installed

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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) has a catalogue minimum of 512 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Treat deepseek-v3.1 as an advanced workstation/server-grade catalogue target with verified GGUF artefacts. Open the GGUF files and follow the upstream runtime notes; LocalClaw does not claim a one-click LM Studio install.

Public GGUF repository (verified 2026-09-23): unsloth/DeepSeek-V3.1-GGUFUpstream releasePaper or model cardLicence text
chatreasoningquality

Deployment path

01
Check RAM fitServer-grade target. Plan for 512 GB class multi-GPU memory.
02
Load the modelOpen the verified GGUF files for deepseek-v3.1 and follow the upstream runtime or patch notes first.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: deepseek-v3
  • Parameters: 671B (37B active, MoE)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 512 GB
  • Catalogue model size: 360 GB
  • Tags: chat, reasoning, quality

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
  • reasoning
  • quality

Capability profile

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

speed
1
quality
10
coding
10
reasoning
10

Technical notes

Developer
DeepSeek AI
License
DeepSeek License
Context window
131,072 tokens
Architecture
Mixture of Experts (MoE) — 671B total, ~37B active

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

Related catalogue entries

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

DeepSeek V3 (671B MoE) 671B (37B active)DeepSeek V3.2 (37B/685B MoE) 685B total (37B active, MoE)DeepSeek V3.2 Exp (671B MoE) 671B (37B active)DeepSeek R1 0528 (671B MoE) 671B (37B active)R1-1776 (671B MoE) 671B (37B active, MoE)

Where to go next