LocalClaw/LLM/Laguna S 2.1
Open-weight MoE

Laguna S 2.1

Catalogue summary: Poolside workstation-class coding MoE with 1M context, 118B total / 8B active parameters, OpenMDW-1.1 licensing and official Q4_K_M GGUF plus Ollama availability.

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

96 GB catalogue minimum96 GB RAMQ4_K_MCoding assistant
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Parameters
118B (8B active, MoE)
Minimum RAM
96 GB
Model size
75.2 GB
Quantization
Q4_K_M

Can Laguna S 2.1 run locally?

Laguna S 2.1 has a catalogue minimum of 96 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use laguna-s-2.1 as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

Model sourcePublic GGUF repository (verified 2026-09-07): poolside/Laguna-S-2.1-GGUFUpstream releasePaper or model cardLicence text
chatcodereasoningagentbeastlong-contexttool-calling

Install path

01
Check RAM fitMinimum 96 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch laguna-s-2.1 in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: laguna
  • Parameters: 118B (8B active, MoE)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 96 GB
  • Catalogue model size: 75.2 GB
  • Tags: chat, code, reasoning, agent, beast, long-context, tool-calling

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
  • code
  • reasoning
  • agent
  • beast
  • long-context

Capability profile

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

speed
3
quality
9
coding
10
reasoning
9

Technical notes

Developer
Poolside
License
OpenMDW-1.1
Context window
1,048,576 tokens
Architecture
118B total parameter Mixture-of-Experts language model with about 8B activated parameters per token, 256 routed experts plus one shared expert, grouped-query attention, and mixed sliding-window plus global attention layers.

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.

Large unified memoryMac Studio M4 Max 128GB128GB AI PC classNVIDIA GB10 / DGX SparkHigh-memory picks128GB RAM guide

Related catalogue entries

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

Laguna XS 2.1 33B (3B active, MoE)Qwen3-Coder-Next 80B (3B active, MoE)Mistral Small 4 (119B-A6.5B) 119B (6.5B active, MoE)Hy3 295B (21B active)LongCat-Flash-Lite 68.5B (3-4.5B active, MoE)GPT-OSS (120B) 117B (5.1B active)K2-Horizon-MoVA-36B-A4B 36B (4B active, MoE)Nanbeige4.2 3B 4B (3B non-embedding)

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