Models on Nesa: Playground and Custom Uploads
Model Playground & Custom Models
The Model Playground is where developers explore, evaluate, and deploy models on Nesa. It combines an extensive on-chain model catalog with the ability to upload and operate custom models directly on the network.
Note: Custom model uploads are currently available to Nesa Pro users only. Pro users may have up to 5 custom models active on the network at any given time.
Model Playground
Nesa maintains a large and continuously growing catalog of on-chain models spanning text, image, video, audio, 3D, bio, and multi-modal tasks.
The Playground allows builders to:
Browse and compare models by modality and task
Inspect performance signals such as latency and usage
Select models for use in DAIs or downstream applications
All models in the Playground run on Nesa’s decentralized inference infrastructure, providing consistent execution and observable performance.
Extensive Model Support
The Model Playground provides access to a large, heterogeneous catalog of production-ready models, spanning language, vision, audio, and video workloads. Models are exposed as first-class on-chain assets, each with clear metadata, performance signals, and usage characteristics.
Out of the box, the Playground includes:
Text and reasoning models Instruction-tuned and reasoning-focused LLMs (e.g., Llama, Qwen, DeepSeek, GPT-family variants) optimized for dialogue, coding, retrieval, and multi-step reasoning, with visible latency and usage statistics.
Image generation models Diffusion and DiT-based models for artistic, photorealistic, and design-oriented generation (e.g., anime-style illustration, typography-aware posters, fast preview models), supporting a wide range of resolutions and inference speeds.
Video generation models Short- and medium-horizon video models designed for cinematic content, storytelling, and animation, with different trade-offs between quality, latency, and clip length.
Audio and speech models Models for speech synthesis, music generation, and audio understanding, exposed with consistent inference and deployment interfaces.
Multi-modal and domain-specific models Models that combine text, vision, or audio inputs, as well as specialized models tuned for branding, design, reasoning, or creative workflows.
Each model card surfaces practical signals such as:
Average inference latency
Community usage and ratings
Supported modality and task
Selection and deployment status
This allows teams to compare, prototype, and deploy models quickly without managing hosting, scaling, or execution pipelines themselves, while retaining the option to upload and operate custom models when needed.
Uploading Custom Models
In addition to the public catalog, Nesa allows developers to upload custom models and run them on the network.
Custom models can be registered through the Build on Nesa flow and configured using:
A Docker image or GitHub repository
Model metadata and description
Modality and task definitions
Visibility and access settings
Once uploaded, custom models become first-class citizens on the network and can be used by DAIs or other applications.
Pro access: Custom model uploads require a Nesa Pro account. Each Pro user may register up to 5 active custom models at a time.
Consistent Execution and Presentation
Uploaded models follow Nesa’s standardized execution and presentation pipeline. This ensures:
Consistent inference behavior across models
Unified UI and metadata for discovery
Compatibility with DAIs, staking, and incentives
Optional features such as encryption, visibility controls, and future access policies can be configured per model.
Summary
The Model Playground gives builders immediate access to a broad ecosystem of on-chain models, while custom model upload enables teams to deploy proprietary or specialized models without operating their own infrastructure.
Together, these capabilities make Nesa a practical environment for building, testing, and scaling decentralized AI applications.
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