NextStep-1

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NextStep-1 is a research project focused on autoregressive image generation using continuous tokens. It explores new methods for generating high-quality images with AI.

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At a glance

Pricing

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Free tier

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API

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Skill level

Technical

About

What is NextStep-1?

NextStep-1 is a research project developed by StepFun’s Multimodal Intelligence team. The project, presented at ICLR 2026, focuses on advancing autoregressive image generation techniques. It specifically investigates the use of continuous tokens to produce high-quality images through artificial intelligence. This research aims to push the boundaries of AI's capabilities in visual content creation.

Best used for

Advancing the state-of-the-art in AI-driven image generation through novel research.

Common actions

Generate images

Research AI models

Explore generative techniques

Advance image synthesis

face swappinggithub copilotworkflowscollaborationautomated workflowdeepfake"AI Agents"low-code/no-codeopen-source

Capabilities

Key features

Autoregressive image generation
Continuous tokens
High-quality image output
AI research project

Target Audience

AI ResearchersMachine Learning EngineersAcademicsGenerative AI Developers

Integrations

Not yet documented

Pricing & Plans

unknown

Free

FAQs

Is NextStep-1 available for public use or commercial applications?

NextStep-1 is currently a research project presented at ICLR 2026 by StepFun’s Multimodal Intelligence team. It is not yet available for public use or commercial applications, as its primary focus is on advancing AI research in autoregressive image generation.

What makes NextStep-1's approach to image generation unique compared to other AI models?

NextStep-1 specifically investigates the use of continuous tokens in autoregressive image generation. This approach aims to produce high-quality images and push the boundaries of AI's capabilities in visual content creation beyond existing methods.

Where can I find the research paper or more technical details about NextStep-1?

As NextStep-1 was presented at ICLR 2026, you would typically find the research paper and detailed technical specifications in the proceedings or archives of the ICLR conference for that year, or on StepFun's Multimodal Intelligence team's official research page.

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