GPT Image 1.5 vs Laguna by Poolside: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of GPT Image 1.5 and Laguna by Poolside — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
GPT Image 1.5
OpenAI
Cost-efficient GPT-5 image generator for high-quality visuals, precise edits, and UI designs up to 4× faster.
Key features
- GPT-5 Powered Generation: Uses GPT-5-based image synthesis capabilities to produce detailed visuals and creative outputs with improved semantic understanding.
- Cost-Efficient Processing: Optimized to reduce compute costs per image, enabling larger-scale generation or lower-priced usage for teams and projects.
- Fast Throughput (Up to 4×): Engineered for accelerated image creation and editing workflows, reducing iteration time for designers and content teams.
- Precise Image Edits: Supports targeted edits and refinements to existing images, enabling corrections and modifications without full re-generation.
- UI Design Output: Tailored to generate UI components and mockups, helping product designers rapidly prototype interfaces and visual assets.
- High-Quality Visuals: Focus on producing clean, high-fidelity images suitable for marketing, product imagery, and design presentations.
- Cost-efficient image generation
- High-quality visual outputs
- Precise image edits
- UI design generation
- Up to 4× faster generation throughput
Best for
- Rapid UI Prototyping: Generate multiple UI mockups and component variations quickly to iterate on app and web interfaces during product design sprints.
- Precise Asset Edits: Apply targeted corrections or enhancements to product photos and marketing images without recreating the entire visual.
- High-Volume Visual Production: Produce large batches of marketing visuals or social media imagery while managing compute costs for startups and agencies.
- Design Exploration: Create diverse concept art and visual directions for branding exercises, enabling fast A/B comparisons of styles and layouts.
- Prototype-to-Presentation Workflow: Turn rough design sketches or briefs into polished visuals for stakeholder demos and pitch materials.
- Cost-Conscious Creative Teams: Allow small teams to scale image generation and iteration without incurring high per-image costs.
- Rapid creation of marketing visuals and illustrations
- Iterative UI and product-design mockups
- Precise image edits and refinements
- Fast prototyping of visual assets for applications and websites
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.