Hy4 preview vs Suno: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Hy4 preview and Suno — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Hy4 preview
Tencent
Tencent's open-weight Hy4 preview, a 770B-parameter Mixture-of-Experts model with 49B active parameters and a 1M-token context window.
Key features
- 770B Mixture-of-Experts Architecture: Holds 770 billion total parameters while activating only 49 billion per token, so capacity scales without proportional inference cost.
- 1M-Token Context Window: Accepts inputs exceeding one million tokens, allowing whole codebases, long document sets or extended agent traces in a single prompt.
- Apache 2.0 Open Weights: Released under a permissive licence that allows commercial use, modification and redistribution with no separate agreement.
- Productivity Task Focus: Tuned for real-world coding, office work and scientific research rather than narrow benchmark optimisation.
- Multi-Product Availability: Accessible globally through Tencent's WorkBuddy, CodeBuddy, Yuanbao and ima applications in addition to the raw weights.
- API Access via TokenHub and OpenRouter: Can be called through Tencent Cloud TokenHub or OpenRouter for teams that prefer hosted inference over self-hosting.
Best for
- Whole-Repository Code Work: Load an entire codebase into the million-token context to reason about refactors and cross-file dependencies at once.
- Long-Horizon Agent Tasks: Drive multi-step agent workflows where the full history of tool calls and intermediate results must stay in context.
- Self-Hosted Deployment: Run a frontier-scale open-weight model on private infrastructure where data cannot leave the organisation.
- Scientific Literature Analysis: Ingest large collections of papers or experimental logs and synthesise findings without chunking the input.
- Office Document Processing: Summarise, draft and restructure long reports, contracts and spreadsheets in enterprise workflows.
- Commercial Fine-Tuning: Adapt the weights for a proprietary product under the Apache 2.0 licence without negotiating a model licence.
Suno
Suno
Create original songs, vocals, and audio quickly from text prompts using Suno's music-generation platform and models.
Key features
- Text-to-Music Generation: Generate full music tracks from natural-language prompts and structured song specifications (style, mood, lyrics), producing instrumental or vocal outputs quickly.
- Vocal Synthesis and Lyrics Support: Create sung or spoken vocal performances from provided lyrics with control over vocalist attributes, harmonies, and vocal effects.
- Fine-Grained Generation Controls: Expose sampling and generation parameters (duration, temperature, topK, topP, classifier-free guidance, tempo, key) to steer quality and style of outputs.
- Model Releases and Tools: Publish and provide access to models and checkpoints (for example the Bark text-to-audio family) that support speech, music, background audio and nonverbal sounds for research and production.
- APIs and Plugin Ecosystem: Integrate Suno capabilities via official/unofficial APIs, community SDKs and plugins (examples include ElizaOS plugin and third-party wrappers) for embedding music generation into apps and agents.
- Audio Editing & Extension: Extend, inpaint or remix existing audio clips and stitch generated segments into longer songs, with metadata and project organization tools offered by community power-tools.
- Community Datasets and Exports: Produce datasets and export metadata for generated songs (used by community datasets like Suno 20K) to aid research, iteration and cataloging of creations.
- Sharing and Discovery: Publish and discover music from other creators on the platform to collaborate, remix, and showcase generated compositions.
- Text-to-music generation from natural language prompts
- Text-to-speech and multi-audio generation via the Bark model (suno/bark, suno/bark-small) on Hugging Face
- Fine-grained generation parameters: duration, temperature, topK, topP, classifier_free_guidance
- Support for instrumental output, sung vocals, and structured song sections (verse, chorus, bridge, drop, outro)
- Vocal tagging and lyric support (vocalist gender, range, harmony, vocal effects)
- Extend/inpaint existing audio tracks and create multi-clip song compositions
- Integrations and plugins (example: @elizaos/plugin-suno for ElizaOS)
- Community/unofficial SDKs and APIs (e.g., gcui-art/suno-api) to call generation services
- Models and processors compatible with Hugging Face Transformers and PyTorch; processor (AutoProcessor) for tokenization and speaker embeddings
- Dataset exports and research artifacts (Suno 20K dataset of generated songs and metadata)
Best for
- Songwriting and Demo Production: Rapidly prototype chord progressions, melodies, and lyrical ideas as full demo tracks or stems to iterate on song concepts.
- Voice and Vocal Layering for Tracks: Generate sung lead vocals, harmonies, or background vocal layers from lyric prompts for use in demos and productions.
- Soundtrack and Background Music for Media: Create custom background music and loops for videos, podcasts, games, and ads with style and tempo control to match scenes.
- App and Agent Integration: Embed music-generation features into apps, virtual assistants, or creative tools via APIs and plugins to provide on-demand audio creation.
- Audio Research and Dataset Creation: Produce large-scale synthetic audio datasets and metadata for research, model training, or evaluation (as seen in community-curated Suno datasets).
- Remixing and Audio Extension: Inpaint, extend or remix existing audio clips—adding bridges, intros, or alternate arrangements to previously recorded material.
- Creative Collaboration and Sharing: Quickly generate musical ideas to share with collaborators, iterate on arrangements, and discover works from other creators on the platform.
- Rapid composition of original music tracks from textual prompts
- Generating sung vocals and lyric-driven songs
- Producing speech, sound effects, and background audio for media
- Integrating music generation into applications, agents, or assistants (e.g., ElizaOS, GPT agents)
- Research and dataset analysis using generated-song corpora
- Workflow automation and project management for multi-clip song creation (community tooling)