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SkyworkAI/Skywork-R1V

0
View on GitHub↗
3,159 stars·281 forks·Python·MIT·13 viewsarxiv.org/abs/2507.06167↗

Skywork R1V

Skywork-R1V4

Features

  • Frontier Reasoning Models - Hybrid reinforcement learning model for multimodal reasoning.
  • Reasoning Models - Vision-capable reasoning model.

Star history

Star history chart for skyworkai/skywork-r1vStar history chart for skyworkai/skywork-r1v

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Skywork R1V

These projects share indexed features with Skywork R1V. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • minimax-ai/minimax-m1MiniMax-AI avatar

    MiniMax-AI/MiniMax-M1

    3,159View on GitHub↗

    MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.

    Python
    View on GitHub↗3,159
  • open-reasoner-zero/open-reasoner-zeroOpen-Reasoner-Zero avatar

    Open-Reasoner-Zero/Open-Reasoner-Zero

    2,095View on GitHub↗

    An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

    Python
    View on GitHub↗2,095
  • deepseek-ai/deepseek-r1deepseek-ai avatar

    deepseek-ai/DeepSeek-R1

    91,996View on GitHub↗

    DeepSeek-R1 is an open-weights large language model focused on advanced reasoning. It uses chain-of-thought processing and internal monologues to solve complex mathematical and logical problems by breaking tasks into sequential, verifiable thought processes. The model is developed using reinforcement learning to optimize reasoning patterns and verify logical steps. It employs a distillation process to transfer these high-performance logic capabilities from a large teacher model into smaller, computationally efficient versions. The training framework incorporates group relative policy optimiz

    View on GitHub↗91,996
  • qwenlm/qwen3QwenLM avatar

    QwenLM/Qwen3

    27,324View on GitHub↗

    Qwen3 is a transformer-based large language model designed as a generative AI foundation for understanding, reasoning, and generating human language. It functions as a comprehensive ecosystem for model training, fine-tuning, and production-ready inference, providing the underlying architecture and weights necessary to build diverse artificial intelligence applications. The project distinguishes itself through extensive support for model quantization and distributed inference, enabling efficient execution across a wide range of hardware from consumer-grade devices to scalable cloud infrastruct

    Python
    View on GitHub↗27,324
Compare all 30 related projects→

Frequently asked questions

What does skyworkai/skywork-r1v do?

Skywork-R1V4

What are the main features of skyworkai/skywork-r1v?

The main features of skyworkai/skywork-r1v are: Frontier Reasoning Models, Reasoning Models.

Which projects share features with skyworkai/skywork-r1v?

Projects with overlapping indexed features include: open-reasoner-zero/open-reasoner-zero — An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model. skyworkai/skywork-or1 — ✊ Unleashing the Power of Reinforcement Learning for Math and Code Reasoners 🤖. deepseek-ai/deepseek-r1 — DeepSeek-R1 is an open-weights large language model focused on advanced reasoning. It uses chain-of-thought processing… minimax-ai/minimax-m1 — MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. qwenlm/qwen3 — Qwen3 is a transformer-based large language model designed as a generative AI foundation for understanding, reasoning,… xiaomimimo/mimo — MiMo: Unlocking the Reasoning Potential of Language Model – From Pretraining to Posttraining.