models/poolside/laguna-s-2-1
P
Poolside·active·free tier available

Poolside Laguna S 2.1

Poolside's efficiency model. Long-context specialist with 1.0M window.

Overall score
3.85
/5.00 · ranked #103
Input
$0.100
per 1M tokens
Output
$0.200
per 1M tokens
Context
1.0M
tokens
Blended
$0.175
3:1 out:in ratio

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Scores by test

Methodology →
Structured Output
5.0
Strategic Analysis
4.0
Constrained Rewriting
3.0
Creative Problem Solving
3.0
Tool Calling
3.0
Faithfulness
4.0
Classification
4.0
Long Context
5.0
Safety Calibration
1.0
Persona Consistency
5.0
Agentic Planning
4.0
Multilingual
5.0
Tabular Data
4.0

What you need to know

Poolside Laguna S 2.1 is an open-weight model optimized for high-precision formatting and massive data ingestion. Its primary technical advantage is the combination of a 1.0M token context window and a perfect 5/5 score in structured output, making it highly reliable for extracting specific schemas from extremely large documents.

At a blended cost of $0.175 per million tokens, the model is positioned as a budget-friendly option for high-volume processing. It delivers strong performance in multilingual tasks, persona consistency, and agentic planning, though it struggles with creative problem solving and constrained rewriting. Developers should be aware of a critical failure in safety calibration, which scored 1/5, indicating a lack of built-in guardrails.

Use this model if you need a low-cost, open-weight solution for processing long-form documents into structured data or maintaining a strict persona across large contexts. Skip this model if your application requires high safety alignment or nuanced creative writing.

Strengths — Top 3

Structured Output5.0/5.0
Long Context5.0/5.0
Persona Consistency5.0/5.0

Relative weaknesses — Bottom 3

Safety Calibration1.0/5.0
Constrained Rewriting3.0/5.0
Creative Problem Solving3.0/5.0

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