Grok vs Laguna by Poolside: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Grok and Laguna by Poolside — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Grok
xAI
Grok is xAI's conversational assistant delivering real-time search, image generation, trend analysis, and conversational responses with a distinct personality.
Key features
- Real-time Web Search: Integrates live web and social data to provide up-to-date answers, enabling Grok to reference current events and trends rather than relying solely on static training data.
- Generative Text with Personality: Produces conversational, context-aware responses with a distinctive witty persona designed to be informative and engaging while aiming for truthfulness.
- Image Generation: Generates images on demand from prompts within the Grok workspace and mobile apps, enabling multimodal creative outputs alongside text responses.
- Trend Analysis and Insights: Provides trend detection, summarization, and analysis of current topics across web and social sources to surface patterns and emerging stories.
- Voice and Multimodal Output: Supports voice responses and multimodal interactions (text, images, voice) for richer, more natural exchanges on supported platforms.
- Developer API & Integrations: Offers an API/console and SDKs (third-party and community SDKs exist) to integrate Grok models and features into applications, with tiered access to larger models.
- Model Variants & Tiers: Provides access to multiple Grok model versions (including larger models for premium tiers) so users can select trade-offs between speed, cost, and capability.
- Mobile & Web Apps: Available as web and native mobile applications (iOS/Android) for conversational use, image generation, and quick access to Grok features.
- Real-time search and up-to-date information retrieval
- Image generation (image creation capabilities)
- Trend analysis and data summarization
- Conversational chat with personality and Grok Voice support
- Open-weights Grok-1 model availability (314B parameters) with JAX example code
- API Console for developers to access Grok programmatically
- Developer documentation and example code / SDKs (third-party SDKs like Grok PHP exist)
- Mobile applications on iOS and Android for end-user access
- Subscription tiers providing access to advanced models (e.g., Grok 4 / SuperGrok tiers)
- Community and open-source resources (GitHub repositories, Hugging Face discussions/releases)
Best for
- Real-time Q&A and Research: Use Grok to answer factual questions and synthesize current information by pulling live web results and summarizing recent developments for research or reporting.
- Content and Creative Generation: Generate written content, social posts, and images for marketing, storytelling, or rapid prototyping of visual concepts using text-to-image features.
- Trend Monitoring and Analysis: Monitor social and news trends, get summarized insights, and receive alerts or summaries for market research, PR, or competitive intelligence.
- Conversational Assistant on Mobile/Web: Deploy Grok as a personal assistant for scheduling, quick lookups, or interactive help via Grok’s web or mobile apps with voice capability.
- Developer Integration and Apps: Integrate Grok via API or SDKs to add conversational interfaces, summarization, or image generation into third-party applications and services.
- Educational Tutoring and Summarization: Provide students and professionals with up-to-date explanations, summaries, and answers that incorporate recent information and examples.
- Interactive Q&A and research with up-to-date answers
- Automated content and image generation for creative workflows
- Trend detection and summarization for market or social analysis
- Customer-facing chatbots and voice assistants in mobile/web apps
- Developer experimentation and model integration via API and SDKs
- Embedding advanced conversational features into applications using provided API Console and community SDKs
Laguna by Poolside
Poolside
Poolside's family of open Mixture-of-Experts foundation models for agentic coding — XS.2 runs locally, M.1 reaches 72.5% on SWE-bench Verified.
Key features
- Two Model Sizes: Laguna XS.2 (33B total / 3B active) and Laguna M.1 (225B total / 23B active) target different latency and capability needs.
- Mixture-of-Experts Architecture: Routes each token through a subset of experts for efficiency at large scale.
- Local Deployment: XS.2 is small enough to run on a Mac with 36 GB of RAM via Ollama under an Apache 2.0 license.
- Strong SWE-bench Results: XS.2 hits 68.2% and M.1 reaches 72.5% on SWE-bench Verified.
- Bundled Coding Agent: Ships 'pool,' a lightweight terminal-based coding agent.
- Agent Client Protocol: Includes a dual ACP client-server used internally for agent RL training and evaluation.
Best for
- Local Agentic Coding: Running XS.2 on a laptop for private, offline code generation and editing.
- High-Capability Code Tasks: Using M.1 for harder, long-horizon software engineering work.
- Self-Hosted Deployments: Building on open weights to avoid third-party API dependencies.
- Research & Fine-Tuning: Adapting permissively licensed weights for custom coding workflows.
- Benchmarking: Evaluating agentic coding performance against SWE-bench Verified and Pro.