Beatoven.ai vs Laguna by Poolside: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Beatoven.ai and Laguna by Poolside — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Beatoven.ai
Beatoven.ai
Royalty-free, mood-driven AI music generator for background tracks tailored to videos, podcasts and games.
Key features
- Mood-Based Composition: Generates music tailored to specified emotions or moods so creators can evoke particular feelings in their content.
- Royalty-Free Licensing: Outputs tracks intended for royalty-free use, allowing creators to use generated music in videos, podcasts, and games without additional licensing.
- API & SDK Access: Public API and SDK resources (public-api repo) enable programmatic composition, integration into apps, and automated music generation workflows after requesting an API key.
- Customizable Background Tracks: Allows creators to produce background music optimized for narrative media (video/podcast/game) with controls for style and suitability.
- Integration Examples & Docs: Public repository includes examples and documentation to help developers implement composition features into projects or pipelines.
- Emotion-Driven Styling: Focuses on crafting pieces that align with a content creator's intended emotional arc, useful for scoring scenes or transitions.
- Web-based music generation for videos, podcasts and games
- Mood-based composition controls to evoke specific emotions
- Royalty-free output suitable for commercial use (as advertised)
- Public API repository (Beatoven/public-api) containing docs, examples and SDK artifacts
- API key gated access — request key via signup or by contacting hello@beatoven.ai
- Example projects and SDK components provided in the public repository to help integration
- Presence on Hugging Face for community/model visibility
Best for
- Video Scoring: Generating background music tracks specifically tailored to the tone and pacing of short-form and long-form videos.
- Podcast Beds: Creating royalty-free ambient or thematic music for podcast intros, outros, and episode backgrounds.
- Game Audio: Producing loopable background music and mood-driven compositions for game levels, menus, or cutscenes.
- Embedded Generation via API: Integrating Beatoven.ai's composition API into content platforms or apps to provide on-demand music generation for user-created media.
- Content Production Workflows: Replacing stock libraries with custom, emotion-aligned music for marketing videos, social posts, and brand storytelling.
- Generate background music tracks for video content and social media
- Produce customizable music beds for podcasts and spoken-word productions
- Create adaptive soundtrack segments for games and interactive experiences
- Integrate music composition into production pipelines via API/SDK
- Prototype music-driven features using example code and SDKs from the public repo
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.