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Models / Poolside / Laguna XS.2

Laguna XS.2 APIOPEN WEIGHTS262K context

by Poolside · text->text · released 2026-04-28

Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai/), their efficient coding agent series.

Get an API key Try in Chat https://api.datallmlab.com/v1
Input / 1M
$0.10
Output / 1M
$0.20
Context
262K
Providers
1
HF downloads · 30d
88.6K
Cheaper than
89% of catalog

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is Laguna XS.2?

Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai/), their efficient coding agent series. It combines tool calling and reasoning capabilities with a compact footprint, offering...

Laguna XS.2 pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

ModelInput / 1MOutput / 1MCache readCache writeContext
Laguna XS.2$0.10$0.20$0.05262K

On output price, Laguna XS.2 is cheaper than 89% of the 309 models in the catalog.

What Laguna XS.2 costs per month

WorkloadTokens in / out (monthly)Est. cost
Support chatbot40M / 12M$6.40
RAG / knowledge base200M / 20M$24.00
Coding agent80M / 25M$13.00
Batch extraction150M / 8M$16.60
Content generation20M / 40M$10.00

Estimate your own monthly cost

= input × $0.10 + output × $0.20 per 1M · pay-as-you-go, computed in your browser.

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

Laguna XS.2 vs alternatives

Pick Laguna XS.2 when you want open weights you can also self-host. If price is the only priority, it is already the cheapest here.
ModelInput / 1MOutput / 1MContextOur test
Laguna XS.2$0.10$0.20262K
Laguna M.1$0.20$0.40262K
UI-TARS 7B $0.10$0.20128K
Ministral 3 14B 2512$0.20$0.20262K
Mistral Small 3.2 24B$0.07$0.20128K

When not to use Laguna XS.2

Specs

Model IDpoolside/laguna-xs.2
Modalitytext->text (input: text)
Context window262,144 tokens
Max output32,768 tokens
Tool / function calling✅ Yes
Structured output (JSON)
Released2026-04-28
Open weightspoolside/Laguna-XS.2 · 88.6K downloads / 316 likes (30d)

How to call Laguna XS.2

from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="poolside/laguna-xs.2",
    messages=[{"role": "user", "content": "Hello"}],
    # supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)
curl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"poolside/laguna-xs.2","messages":[{"role":"user","content":"Hello"}]}'
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "poolside/laguna-xs.2",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Laguna XS.2 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Laguna XS.2

Tips are derived from Laguna XS.2's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Laguna XS.2

Popular open-source projects for running and building with Laguna XS.2 — star counts pulled from GitHub (July 2026).

ollama/ollama★ 175.3K
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Go
langgenius/dify★ 147.5K
Production-ready platform for agentic workflow development.
TypeScript
open-webui/open-webui★ 144.0K
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Python
langchain-ai/langchain★ 140.8K
The agent engineering platform.
Python
ggml-org/llama.cpp★ 119.1K
LLM inference in C/C++
C++
vllm-project/vllm★ 85.2K
A high-throughput and memory-efficient inference and serving engine for LLMs
Python

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to Laguna XS.2

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → poolside/laguna-xs.2. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Laguna XS.2 ships open weights (poolside/Laguna-XS.2, ~88.6K downloads and 316 likes in the last 30 days), with community quantizations (fp8) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 1 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.

Related reading

How OpenAI-Compatible APIs Work
DataLLM Lab Blog
We Benchmarked LLM Coding Cost & Quality
DataLLM Lab Blog
Best LLM API in 2026: A Buyer’s Guide
DataLLM Lab Blog

Call Laguna XS.2 with one key

300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.

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Frequently asked questions

What is Laguna XS.2?

Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai/), their efficient coding agent series. It accepts text input with a 262K-token context window and was released on 2026-04-28. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.

How much does Laguna XS.2 cost?

On DataLLM Lab it is $0.10 per 1M input tokens and $0.20 per 1M output tokens, with cached input at $0.05/1M — cheaper than about 89% of the 309-model catalog on output price. Pay-as-you-go, no subscription.

What is the context window of Laguna XS.2?

262K tokens, with up to 33K max output tokens.

Is Laguna XS.2 open source?

Yes — open weights are published on Hugging Face (poolside/Laguna-XS.2), with about 88.6K downloads and 316 likes in the last 30 days. You can self-host it or call it via DataLLM Lab.

How do I call the Laguna XS.2 API?

Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "poolside/laguna-xs.2". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.

What are good alternatives to Laguna XS.2?

Close options by price and capability include Laguna M.1, UI-TARS 7B , Ministral 3 14B 2512 — all callable with the same DataLLM Lab key.