How much does Laguna XS 2.1 cost per million tokens?
As of August 20, 2026, Laguna XS 2.1 Poolside API pricing is $0.10 per million input tokens and $0.20 per million output tokens. Input tokens are the prompt you send; output tokens are the completion. Long answers therefore cost more than short ones even when the prompt stays the same. Source: https://poolside.ai
What is the blended API cost for Laguna XS 2.1?
On this page the blended Laguna XS 2.1 API cost is $0.30 for 1 million input tokens plus 1 million output tokens. That 1:1 mix is the comparison scale used across the LLM pricing table. A 3:1 mix (three million input tokens per one million output tokens), which some calculators use, would be about $0.50.
How much does a typical Laguna XS 2.1 request cost?
A typical Laguna XS 2.1 API request with 100K input tokens and 20K output tokens costs about $0.01 at current rates as of August 20, 2026. Multiply that by daily or monthly volume to estimate spend. Caching, batch APIs, and volume discounts from Poolside can bring the real invoice lower than the public list rate at https://poolside.ai.
What is the context window for Laguna XS 2.1?
Laguna XS 2.1 supports a 262K token context window. The context window is the total prompt plus conversation history the model can see in one call. Larger windows cost more when you fill them, because every input token is billed per million tokens.
Is Laguna XS 2.1 open source?
Yes. Laguna XS 2.1 is an open-weight model by Poolside. You can download the weights and self-host, or pay Poolside's hosted API and skip GPU ops. Hosted API pricing on this page is the public per-million-token rate, not the electricity cost of running the weights yourself.
What benchmarks does Laguna XS 2.1 perform well on?
Laguna XS 2.1 currently reports SWE-bench Verified 70.9%, SWE-bench Multilingual 63.1%, Terminal-Bench 2.0 37.5%. See the performance table for the full eval set. Use those scores with the token prices above when you are choosing between a cheaper LLM and a frontier model. GPQA, SWE-bench, and HLE are the evals people usually compare first.
Is Laguna XS 2.1 good for coding?
Laguna XS 2.1 scores 70.9% on SWE-bench Verified. Pair that score with Poolside API pricing on this page: a slightly worse SWE-bench model can still win if it is much cheaper per million tokens. Open the SWE-bench or coding leaderboard from the sidebar for the full ranking, then jump into an LLM comparison against a coding specialist.
How do I compare Laguna XS 2.1 with another LLM?
Use the Compare picker on this page to start an LLM comparison. Search by model or provider, pick a second model, and AnotherWrapper opens a dedicated Laguna XS 2.1 vs page with per-million-token prices, blended 1M-in / 1M-out cost, context window, throughput, and benchmarks. You can also open any model from the sidebar, or go back to the LLM pricing table to sort the full index.
What are the cheapest alternatives to Laguna XS 2.1?
The cheapest LLM alternative depends on whether you optimize for blended token cost, coding evals, or context window. Start with the popular matchups on this page, then sort the LLM pricing table by blended cost to see which hosted APIs undercut Laguna XS 2.1. Open-weight models can be cheaper still if you self-host, but that is not the same as Poolside API pricing on this page.
How do I use Laguna XS 2.1 in my application?
Laguna XS 2.1 is called through Poolside's API with an API key. Bill against input and output tokens separately; cache or shorten prompts if spend is high. If you are shipping a full product, AnotherWrapper includes pre-built API routes and templates for Poolside and 5+ other providers with auth, payments, and deployment already configured.
How accurate is this Laguna XS 2.1 pricing data?
This Laguna XS 2.1 page tracks the latest published Poolside API pricing from Poolside, quoted per million tokens. List rates can differ from invoices because of prompt caching, batch discounts, committed-use tiers, and private contracts. Official rate sheet: https://poolside.ai. Benchmark scores come from official publications and independent evals, not from a private lab run by AnotherWrapper.