Laguna XS 2.1

Laguna XS 2.1

Poolside
+
+

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About

Laguna XS 2.1 is an upgraded open weight agentic coding model designed for long-horizon work on a local machine. It uses a 33-billion-parameter Mixture-of-Experts architecture with 3 billion activated parameters per token, retaining the same efficient architecture as Laguna XS.2 while improving multilingual software engineering and terminal-style task performance. The model is built to support coding agents that inspect repositories, reason through complex changes, use tools, execute commands, and continue working across extended tasks. It is served with a 256K context window, giving agents room to work with large codebases, lengthy histories, and multi-step workflows. Laguna XS 2.1 is supported by vLLM, SGLang, NVIDIA TensorRT-LLM, Hugging Face Transformers, and Ollama, with native llama.cpp support planned. It is available in BF16, FP8, INT4, and NVFP4 checkpoints, allowing developers to choose between maximum fidelity and configurations suited to tighter VRAM or compute budgets.

About

vLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Local-first developer tooling teams that need an efficient open model for persistent coding agents on limited hardware

Audience

AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Poolside
Founded: 2023
United States
poolside.ai/blog/introducing-laguna-xs-2-1

Company Information

vLLM
United States
vllm.ai

Alternatives

Alternatives

OpenVINO

OpenVINO

Intel
Mistral Large 3

Mistral Large 3

Mistral AI
Laguna S 2.1

Laguna S 2.1

Poolside

Categories

Categories

Integrations

Hugging Face
Agent Client Protocol (ACP)
Claude Code
Cline
IntelliJ IDEA
Kilo Code
Kubernetes
NGINX
NVIDIA DRIVE
Nous Portal
Ollama
OpenAI
OpenAI Codex
OpenClaw
Poolside
Roo Code
Thunder Compute
Visual Studio
Zed
omp

Integrations

Hugging Face
Agent Client Protocol (ACP)
Claude Code
Cline
IntelliJ IDEA
Kilo Code
Kubernetes
NGINX
NVIDIA DRIVE
Nous Portal
Ollama
OpenAI
OpenAI Codex
OpenClaw
Poolside
Roo Code
Thunder Compute
Visual Studio
Zed
omp
Claim Laguna XS 2.1 and update features and information
Claim Laguna XS 2.1 and update features and information
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Claim vLLM and update features and information