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

NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.

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

Machine learning engineers and data scientists seeking a tool to optimize their deep learning operations

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

Free
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

NVIDIA
Founded: 1993
United States
developer.nvidia.com/tensorrt

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
CUDA
Dataoorts GPU Cloud
Hermes Agent
Kilo Code
Kimi K2
Kimi K3
NVIDIA Broadcast
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Merlin
NVIDIA NIM
Ollama
PyTorch
RankLLM
Roo Code
Rosepetal AI
Ultralytics
Visual Studio
Visual Studio Code

Integrations

Hugging Face
CUDA
Dataoorts GPU Cloud
Hermes Agent
Kilo Code
Kimi K2
Kimi K3
NVIDIA Broadcast
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Merlin
NVIDIA NIM
Ollama
PyTorch
RankLLM
Roo Code
Rosepetal AI
Ultralytics
Visual Studio
Visual Studio Code
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 NVIDIA TensorRT and update features and information