Gemini 2.5 Flash Image (Nano banana) vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Gemini 2.5 Flash Image (Nano banana) and Hy4 preview — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Gemini 2.5 Flash Image (Nano banana)
State-of-the-art image generation and editing model that blends images, preserves character consistency, and performs targeted edits from natural-language prompts.
Key features
- Multi-Image Blending: Blend and compose multiple input images into a single coherent result while preserving spatial relationships and photo realism for complex collages and composite edits.
- Character Consistency: Maintain the same character appearance across multiple edits and different outputs to ensure consistent identity, outfit, and facial features for serialized imagery or character assets.
- Natural-Language Targeted Transformations: Apply precise edits (e.g., change clothing color, add accessories, modify background elements) by issuing plain-language instructions instead of manual masks or layer edits.
- Zero-Shot High-Fidelity Editing: Perform high-quality edits without task-specific fine-tuning or extensive prompt engineering, reducing the need for separate inpainting models or multi-step toolchains.
- Platform Integration: Available via Gemini API, Google AI Studio, and Vertex AI, enabling programmatic generation and enterprise deployment with existing Google Cloud workflows.
- Grounded World Knowledge: Leverages Gemini's multimodal understanding and knowledge to perform context-aware edits and generate semantically appropriate content based on prompts.
- Resolution & Rate Constraints Awareness: Operates within API-imposed resolution and rate limits (community reports cite ~1024px max dimension) and includes cost/rate behaviors tied to subscription tiers.
- Production Readiness: Designed for creative production and developer workflows with support for composition, iterative edits, and integration into UIs and pipelines through SDKs and community adapters (ComfyUI, MCP servers).
- Prompt-driven text-to-image generation with high visual fidelity
- Zero-shot image editing: apply natural-language edits to uploaded images
- Compositional operations: blend, mask, and compose multiple elements in one pass
- Maintains character and face consistency across edits
- Fast ‘Flash’ inference mode for lower-latency results
- API-first access via Google Gemini API / Google AI Studio
- Client library compatibility: Python (google-genai), Node/TypeScript examples and SDKs
- Community integrations: ComfyUI custom node, MCP proxy for Claude, Next.js/React frontends
- Configurable response formats (e.g., JSON) and file upload endpoints
- Operational constraints exposed by community: ~1024px max output dimension, subscription-dependent rate limits
Best for
- Marketing Creative Production: Rapidly generate and iterate high-quality campaign images, produce multiple variants (color, props, backgrounds) from a single concept, and keep brand characters visually consistent across assets.
- Character & Asset Design: Create consistent character portraits and variations for games, comics, or animation by preserving facial features and costume details across edits and poses.
- Photo Editing & Retouching: Apply targeted edits (e.g., change clothing color, add glasses, remove objects) using natural-language instructions while preserving face and scene integrity.
- E-commerce Imaging: Generate product photos with consistent lighting and backgrounds or create styled variations (different colors, model poses) to scale catalog imagery.
- Concept Art & Storyboarding: Compose scenes from multiple source images and rapidly prototype visual concepts, maintaining continuity of characters and visual motifs across frames.
- Tooling & Integration: Embed image generation and editing into apps or pipelines via the Gemini API, Google AI Studio, or Vertex AI for automated content workflows and interactive design tools.
- Community Experimentation & Research: Use community adapters (ComfyUI nodes, MCP servers) to explore prompt engineering, advanced composition techniques, and comparisons with other image models.
- Creative artwork generation and concept art from natural-language prompts
- Photo editing and retouching using descriptive instructions
- Character-consistent iterative edits for comics, games, and IP assets
- Automated content production for marketing, social media, and advertising
- Rapid prototyping and visual mockups in design workflows
- Compositional scene creation and storyboarding
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.