Koyal vs Laguna by Poolside: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Koyal and Laguna by Poolside — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Koyal
Koyal
Converts audio or scripts into end-to-end cinematic videos with generated characters, settings, storylines and animations.
Key features
- End-to-End Audio-to-Video: Converts raw audio or written scripts into fully rendered cinematic videos without manual storyboard assembly, handling scene sequencing, camera framing and transitions.
- Personalized Character Generation: Creates custom characters, including user likenesses, with consistent appearances and behaviors across scenes to maintain narrative continuity.
- Automated Setting and Scene Design: Generates coherent environments and background elements matched to the story tone and audio cues, ensuring visual consistency across sequences.
- Agentic Filmmaking Pipeline: Orchestrates multi-step production tasks (scripting, casting, scene planning, animation) automatically while exposing controls for user-driven creative adjustments.
- Storyline and Dialogue Alignment: Produces story structure, pacing and visual beats that align with audio content and dialogue to create cinematic narrative flow.
- Fast Iteration and Rendering: Designed for quick turnaround, enabling users to produce animated film clips and prototypes within minutes rather than hours or days.
- Safety and Content Controls: Incorporates safeguards and content moderation to support safer AI-generated video creation (as highlighted by the developer and partner coverage).
- Convert audio or script into end-to-end cinematic video automatically
- Generate consistent storylines, settings, and characters in one workflow
- Create personalized characters/avatars (including representations of the user)
- Automated scene and animation generation to produce finished clips
- Web-based platform with account sign-up and beta access
- Safety-focused generation tools and creative control for users
Best for
- Podcast-to-Video Conversion: Transform full podcast episodes or clips into cinematic video shorts with animated scenes and characters for social sharing.
- Personalized Storytelling: Generate short films or narrative videos that include a user's likeness or custom characters for gifts, marketing, or social content.
- Marketing and Ad Production: Rapidly produce branded video ads or promotional stories from a script or audio brief without hiring a production crew.
- Prototype Filmmaking: Quickly visualise scripts and story ideas as animated proofs-of-concept to pitch to stakeholders or iterate on story beats.
- Educational Content Creation: Convert lectures or audio lessons into engaging animated videos that illustrate concepts with contextual scenes and characters.
- Content Repurposing for Creators: Repurpose existing audio content (interviews, voiceovers) into multiple visual formats tailored for different platforms.
- Turn podcast episodes or voice recordings into cinematic visual stories
- Rapid prototyping of film scenes and storyboards from scripts or audio
- Create personalized social videos and marketing content with custom characters
- Educational or explainer videos generated from narrated scripts
- Generate animated character-driven short films or vignettes from audio
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.