# Laguna S 2.1 Usage, Cost & Rank | OpenCode Data

> Laguna S 2.1 had 0.0% of tokens across OpenCode over the past two months. Laguna S 2.1 costs $0.09 per 1M input tokens and $0.18 per 1M output tokens.

Agentic coding model from Poolside in the XS size class for local deployment

- Page: https://opencode.ai/data/poolside/laguna-s-2-1
- JSON: https://opencode.ai/data/poolside/laguna-s-2-1.json
- Model ID: poolside/laguna-s-2.1
- Lab: Poolside
- Updated: 2026-10-22T01:40:05.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 33K |
| Knowledge cutoff | - |
| Release date | 2026-07-21 |
| Input modalities | text |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | Yes |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.09 | $0.18 | $0.0090 | - |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | Unranked |
| Tokens | 208B |
| Share of all tokens | 0.0% |
| Change vs previous 2 months | -77% |
| Unique users | 29K |
| Completed sessions | 1,661,741 |
| Average tokens per session | 125K |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 83.6% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-29 | 24B | 3.7K | 301,482 |
| 2026-08-30 | 26B | 4.2K | 401,434 |
| 2026-08-31 | 30B | 4K | 226,099 |
| 2026-09-01 | 33B | 3.8K | 133,739 |
| 2026-09-02 | 32B | 3.8K | 169,469 |
| 2026-09-03 | 30B | 4.2K | 194,177 |
| 2026-09-04 | 28B | 4K | 191,047 |
| 2026-09-05 | 4.6B | 1.1K | 43,674 |
| 2026-09-06 | 0 | 0 | 0 |
| 2026-09-07 | 0 | 0 | 1 |
| 2026-09-08 | 0 | 0 | 3 |
| 2026-09-09 | 0 | 0 | 1 |
| 2026-09-10 | 0 | 0 | 1 |
| 2026-09-11 | 0 | 0 | 1 |
| 2026-09-12 | 0 | 0 | 3 |
| 2026-09-13 | 0 | 0 | 2 |
| 2026-09-14 | 0 | 0 | 2 |
| 2026-09-15 | 0 | 0 | 1 |
| 2026-09-16 | 0 | 0 | 4 |
| 2026-09-17 | 0 | 0 | 6 |
| 2026-09-18 | 0 | 0 | 78 |
| 2026-09-19 | 0 | 0 | 290 |
| 2026-09-20 | 0 | 0 | 227 |
| 2026-09-21 | 0 | 0 | 0 |
| 2026-09-22 | 0 | 0 | 0 |
| 2026-09-23 | 0 | 0 | 0 |
| 2026-09-24 | 0 | 0 | 0 |
| 2026-09-25 | 0 | 0 | 0 |
| 2026-09-26 | 0 | 0 | 0 |
| 2026-09-27 | 0 | 0 | 0 |
| 2026-09-28 | 0 | 0 | 0 |
| 2026-09-29 | 0 | 0 | 0 |
| 2026-09-30 | 0 | 0 | 0 |
| 2026-10-01 | 0 | 0 | 0 |
| 2026-10-02 | 0 | 0 | 0 |
| 2026-10-03 | 0 | 0 | 0 |
| 2026-10-04 | 0 | 0 | 0 |
| 2026-10-05 | 0 | 0 | 0 |
| 2026-10-06 | 0 | 0 | 0 |
| 2026-10-07 | 0 | 0 | 0 |
| 2026-10-08 | 0 | 0 | 0 |
| 2026-10-09 | 0 | 0 | 0 |
| 2026-10-10 | 0 | 0 | 0 |
| 2026-10-11 | 0 | 0 | 0 |
| 2026-10-12 | 0 | 0 | 0 |
| 2026-10-13 | 0 | 0 | 0 |
| 2026-10-14 | 0 | 0 | 0 |
| 2026-10-15 | 0 | 0 | 0 |
| 2026-10-16 | 0 | 0 | 0 |
| 2026-10-17 | 0 | 0 | 0 |
| 2026-10-18 | 0 | 0 | 0 |
| 2026-10-19 | 0 | 0 | 0 |
| 2026-10-20 | 0 | 0 | 0 |
| 2026-10-21 | 0 | 0 | 0 |
| 2026-10-22 | 0 | 0 | 0 |
| 2026-10-23 | 0 | 0 | 0 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 32B | 15.5% |
| 2 | Indonesia | 25B | 12.2% |
| 3 | China | 18B | 8.7% |
| 4 | Brazil | 12B | 5.6% |
| 5 | India | 12B | 5.6% |
| 6 | Germany | 11B | 5.2% |
| 7 | Singapore | 7.9B | 3.8% |
| 8 | Azerbaijan | 7.6B | 3.7% |
| 9 | Netherlands | 5.8B | 2.8% |
| 10 | France | 4.9B | 2.3% |
| 11 | Vietnam | 4B | 1.9% |
| 12 | Canada | 3.5B | 1.7% |
| 13 | Japan | 3.4B | 1.6% |
| 14 | United Kingdom | 3.2B | 1.6% |
| 15 | Spain | 2.8B | 1.3% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 1 | [deepseek-v4.1-flash](https://opencode.ai/data/deepseek/deepseek-v4-1-flash.md) | DeepSeek | 106T |
| 2 | [minimax-m3.1-flash](https://opencode.ai/data/minimax/minimax-m3-1-flash.md) | MiniMax | 42T |
| 3 | [glm-5.3-flash](https://opencode.ai/data/zhipuai/glm-5-3-flash.md) | Zhipu | 8.9T |
| 4 | [mimo-v2.6-flash](https://opencode.ai/data/xiaomi/mimo-v2-6-flash.md) | Xiaomi | 8.3T |
| 5 | [muse-spark-1.3-contributor](https://opencode.ai/data/meta/muse-spark-1-3-contributor.md) | Meta | 7.2T |
| 6 | [beam](https://opencode.ai/data/reflection/beam.md) | Reflection | 4.8T |
| 7 | [nemotron-3-ultra](https://opencode.ai/data/nvidia/nemotron-3-ultra.md) | NVIDIA | 3.2T |
| 8 | [nemotron-3.5-super-vl](https://opencode.ai/data/nvidia/nemotron-3-5-super-vl.md) | NVIDIA | 2.1T |
| 9 | [longcat-2.5-preview](https://opencode.ai/data/meituan/longcat-2-5-preview.md) | Meituan | 1.5T |
| 10 | [deepseek-v4-flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md) | DeepSeek | 978B |

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.