Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Laguna XS.2 represents Poolside’s innovative open-weight coding model, distinguished as the lightest and quickest member of the Laguna series. This model features a total of 33 billion parameters in a Mixture of Experts setup, with 3 billion parameters activated, and has been meticulously trained in-house using 30 trillion tokens. As the latest generation model accessible to the public, it embodies a second-generation architecture and marks Poolside’s inaugural open-weight offering, drawing from insights gained during the training of Laguna M.1 with synthetic data and reinforcement learning techniques. Specifically designed to enhance agentic coding workflows, Laguna XS.2 excels in coding, acting, and rapidly iterating, particularly within Poolside’s coding agent environment. This model is particularly advantageous for developers and teams seeking a lightweight, efficient coding solution rather than a more cumbersome frontier system. Released under the permissive Apache 2.0 license, it empowers the community to assess, fine-tune, quantize, and build upon its weights, fostering a collaborative development atmosphere. In essence, Laguna XS.2 not only provides a robust platform for agentic coding but also encourages innovation and experimentation among its users.

Description

Ling 3.0 Tiny is a reasoning model featuring open weights, comprising 7.9 billion total parameters and 1.3 billion active parameters, alongside a substantial context window of 262,000 tokens. Leveraging a mixture-of-experts architecture, it pushes the boundaries of the open-weights Pareto frontier in terms of intelligence relative to active parameters, while being compact enough for local deployment in various environments. Scoring 25 on the Artificial Analysis Intelligence Index, it stands on par with gpt-oss-120b, which scores 24, despite utilizing 15 times fewer total parameters and 4 times fewer active parameters. This impressive parameter efficiency does come with a trade-off, as it requires a significant 213 million output tokens to complete the Intelligence Index evaluation. In addition, Ling 3.0 Tiny exhibits noteworthy advancements in reducing hallucination tendencies compared to Ling-mini-2.0; it enhances its AA-Omniscience score by 59 points while keeping accuracy levels consistent. Notably, rather than making random guesses in uncertain situations, the model chose to attempt only 37% of the questions during evaluation, leading to a markedly reduced hallucination rate of 30%, a significant improvement over the previous generation's 96%. This strategic approach not only demonstrates the model's improved reasoning capabilities but also highlights its potential for more reliable real-world applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Claude Code
Hermes Agent
Kilo Code
OpenClaw
OpenRouter
Agent Client Protocol (ACP)
Cline
Hugging Face
IntelliJ IDEA
Nous Portal
Ollama
OpenAI Codex
OpenCode
Poolside
Roo Code
Visual Studio
Visual Studio Code
Zed
ZenMux

Integrations

Claude Code
Hermes Agent
Kilo Code
OpenClaw
OpenRouter
Agent Client Protocol (ACP)
Cline
Hugging Face
IntelliJ IDEA
Nous Portal
Ollama
OpenAI Codex
OpenCode
Poolside
Roo Code
Visual Studio
Visual Studio Code
Zed
ZenMux

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Poolside

Founded

2023

Country

United States

Website

www.poolside.ai/models

Vendor Details

Company Name

Ant Group

Founded

2014

Country

China

Website

ant-ling.com

Product Features

Product Features

Alternatives

Alternatives

Kimi K3 Reviews

Kimi K3

Moonshot AI
GLM-5.2 Reviews

GLM-5.2

Zhipu AI
GLM-5.2 Reviews

GLM-5.2

Zhipu AI
Laguna M.1 Reviews

Laguna M.1

Poolside
Ling 2.6 Flash Reviews

Ling 2.6 Flash

Ant Group
Kimi K2.7 Code Reviews

Kimi K2.7 Code

Moonshot AI
Qwen3.8-Max Reviews

Qwen3.8-Max

Alibaba