de Poolside hyper-efficient codage modèle développé pour instant linting, unit test synthèse, et élevé-frequency développeur flux de travail.
Technical Specifications
- Provider
- Poolside
- Category
- lightweight
- Release Date
- 2026-07
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- laguna-xs-2-1
- Supported SDK & API Protocol
- Poolside REST API (OpenAI-Compatible)
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2028+)
- Production Rate Limits (RPM & TPM)
- 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.05/1M in) across full 262K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.005/1M tokens
- Computer Use & Browser GUI Agent
- API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
- MCP & Parallel Tool Calling
- Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- API Prompt Engineering & RAG Distillation
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed Poolside Cloud API
- System Card & Safety Framework
- Poolside Production Safety & Alignment Verified
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Laguna XS 2.1 Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $15.35/mo vs $20 flat plan).
Break-even point: ~2,151 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Laguna XS 2.1:
Benchmark Scores & 6-Axis Capability Radar
- MMLU-Pro
- 74%
- HumanEval
- 88%
- LiveCodeBench
- 64%
- Chatbot Arena Elo
- 1280pts
Strengths
- ultra-cheap tarification ($0.05 / 1M entrée) tailored pour continuous développeur intégration
- élevé codage précision sur quotidien scripts, boilerplate, et test cases
- sous-250ms latence ideal pour inline IDE code suggestions
Limitations & Trade-offs
- pas conçu pour général non-programmation topics ou créatif writing
- Struggles avec grand-échelle distributed systems architectural planning
Editorial Assessment
un ultra-rapide codage specialist offrant haut de gamme-notch efficacité à bargain tarification.
Best for: IDE autocompletion, CI/CD automatisé test génération, et pull request syntax checking
Compare Laguna XS 2.1
Frequently Asked Questions about Laguna XS 2.1
How much does the Laguna XS 2.1 API cost per 1M tokens?+
Laguna XS 2.1 by Poolside is priced at $0.05 per 1M input tokens and $0.2 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.005 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Laguna XS 2.1 pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Laguna XS 2.1's context window?+
Laguna XS 2.1 features a 262K tokens context window, which equals approximately 196,608 English words or ~524 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.
Can I run Laguna XS 2.1 locally on my own GPU (Open Weights)?+
No, Laguna XS 2.1 is a proprietary closed-weights model hosted by Poolside. It cannot be downloaded for local GPU execution and must be accessed via Poolside's official API or cloud platform.
Does Poolside train on data sent to the Laguna XS 2.1 API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Poolside Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Poolside Cloud API & Enterprise Endpoints.
How does Laguna XS 2.1 perform on coding and reasoning benchmarks?+
Laguna XS 2.1 achieves a composite Intelligence Index of 77/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 74% on MMLU-Pro, and 1280 pts on Chatbot Arena Elo.
What is Laguna XS 2.1 best used for?+
Laguna XS 2.1 is best suited for: IDE autocompletion, CI/CD automatisé test génération, et pull request syntax checking. Assessment: un ultra-rapide codage specialist offrant haut de gamme-notch efficacité à bargain tarification.
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Laguna XS 2.1:
L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.
Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).
Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.
Un modèle d'IA entraîné par apprentissage par renforcement pour allouer du temps de calcul à la réflexion logique avant d'émettre une solution, idéal pour les problèmes scientifiques et le code complexe.
Une méthode de raisonnement pas-à-pas où le modèle décompose le problème en étapes logiques intermédiaires avant de conclure, augmentant drastiquement la précision en mathématiques et programmation.
La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.
Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: Poolside Developer Release↗