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What is Step 3.5 Flash?

Step 3.5 Flash represents a state-of-the-art open-source foundational language model crafted for sophisticated reasoning and agent-like functionality, prioritizing efficiency; it employs a sparse Mixture of Experts (MoE) framework that activates roughly 11 billion of its nearly 196 billion parameters for each token, which ensures both dense intelligence and rapid responsiveness. The architecture includes a 3-way Multi-Token Prediction (MTP-3) system, enabling the generation of hundreds of tokens per second and supporting intricate multi-step reasoning and task execution, while efficiently handling extensive contexts through a hybrid sliding window attention technique that reduces computational stress on large datasets or codebases. Its remarkable capabilities in reasoning, coding, and agentic tasks often rival or exceed those of much larger proprietary models, further enhanced by a scalable reinforcement learning mechanism that promotes ongoing self-improvement. This innovative design not only highlights Step 3.5 Flash's effectiveness but also positions it as a transformative force in the domain of AI language models, indicating its vast potential across a plethora of applications. As such, it stands as a testament to the advancements in AI technology, paving the way for future developments.

What is LongCat-2.0?

LongCat-2.0 signifies a remarkable leap forward in the field of language models, boasting an impressive 1.6 trillion parameters through a Mixture-of-Experts architecture that utilizes AI ASIC superpods, with around 48 billion parameters activated per token, demonstrating outstanding proficiency in coding and agentic functions. This model notably surpasses its predecessors by incorporating a large-scale sparse architecture along with specialized post-training techniques designed specifically for applications in real-world software development, tool usage, long-context reasoning, and intricate agent operations. Entirely built and executed on AI ASIC superpods, LongCat-2.0's pretraining involved processing over 35 trillion tokens and countless accelerator hours, highlighting the forefront of training techniques on state-of-the-art hardware. To further enhance its capabilities on tasks that require long-term contextual awareness, the model integrates LongCat Sparse Attention and is trained with hundreds of billions of tokens derived from 1M-context datasets, which empowers it to adeptly handle ultra-long context challenges and maintain a comprehensive understanding of extensive documents. This unique blend of features not only establishes LongCat-2.0 as an innovative leader in advanced language models but also sets a new benchmark for future developments in the domain. Its capabilities are likely to inspire a new wave of research and applications in the field.

Media

Media

Integrations Supported

Claude Code
GitHub
Hermes Agent
Hugging Face
ModelScope
OpenClaw
arXiv

Integrations Supported

Claude Code
GitHub
Hermes Agent
Hugging Face
ModelScope
OpenClaw
arXiv

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

StepFun

Date Founded

2023

Company Location

China

Company Website

static.stepfun.com/blog/step-3.5-flash/

Company Facts

Organization Name

LongCat

Date Founded

2023

Company Location

China

Company Website

longcat.chat/blog/longcat-2.0/

Categories and Features

Categories and Features

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