Tülu 3 405B

(Be the first to comment)
Tülu3 is a leading instruction following model family, offering fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern post-training techniques. Tülu3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.0
Visit website

What is Tülu 3 405B?

Tülu 3 405B is the latest advancement in open-weight AI models, designed to push the boundaries of performance and scalability. Building on the success of the Tülu 3 release, this model leverages a fully open post-training recipe at an unprecedented 405 billion parameter scale. It outperforms leading models like DeepSeek V3 and GPT-4o, as well as other open-weight models such as Llama 3.1 405B Instruct and Nous Hermes 3 405B, across multiple benchmarks.

At its core, Tülu 3 405B demonstrates the power of Reinforcement Learning with Verifiable Rewards (RLVR), a novel framework that enhances specific skills like mathematical problem-solving and instruction following. This release not only showcases the scalability of RLVR but also highlights its effectiveness in improving performance at larger model sizes.

Key Features of Tülu 3 405B

🧠 Scalable Reinforcement Learning with Verifiable Rewards (RLVR):
RLVR is a groundbreaking approach that trains models using tasks with verifiable outcomes. By focusing on MATH data, Tülu 3 405B achieves significant improvements in mathematical problem-solving, especially at larger scales.

📊 Superior Benchmark Performance:
Tülu 3 405B consistently outperforms competing models, including DeepSeek V3 and GPT-4o, across a range of evaluation benchmarks. It also excels in safety benchmarks, making it a reliable choice for real-world applications.

🔧 Robust Training Infrastructure:
The model was trained using 256 GPUs across 32 nodes, with 16-way tensor parallelism for inference. Despite technical challenges like NCCL timeout issues, the training pipeline proved resilient, enabling the release of the largest open-recipe model to date.

📈 Efficient Hyperparameter Tuning:
Following the principle of lower learning rates for larger models, Tülu 3 405B was optimized for stability and performance, even with limited hyperparameter tuning.

How Tülu 3 405B Stands Out

  1. Open and Transparent:
    Unlike many proprietary models, Tülu 3 405B is built on a fully open post-training recipe, making it accessible for researchers and developers to explore and build upon.

  2. Specialized for Complex Tasks:
    The model’s focus on MATH data and RLVR training ensures superior performance in tasks requiring deep reasoning and verifiable outcomes.

  3. Scalable and Future-Ready:
    The success of Tülu 3 405B at 405B parameters demonstrates the scalability of its training framework, paving the way for even larger models in the future.

Use Cases for Tülu 3 405B

  1. Mathematical Problem-Solving:
    Tülu 3 405B excels in solving complex mathematical problems, making it ideal for educational tools, research, and data analysis.

  2. Instruction Following:
    With its RLVR framework, the model can accurately follow and execute detailed instructions, enhancing its utility in automation and workflow optimization.

  3. AI Research and Development:
    As an open-weight model, Tülu 3 405B provides a valuable resource for researchers exploring large-scale AI training and post-training techniques.

Conclusion

Tülu 3 405B represents a significant leap forward in AI model performance and scalability. By combining open post-training recipes with the innovative RLVR framework, it delivers superior results across a wide range of benchmarks. Whether you’re tackling complex mathematical problems or developing cutting-edge AI applications, Tülu 3 405B offers the tools and performance you need to succeed.

FAQ

Q: How does Tülu 3 405B compare to GPT-4o?
A: Tülu 3 405B achieves competitive or superior performance to GPT-4o across multiple benchmarks, particularly in mathematical problem-solving and safety evaluations.

Q: What makes RLVR unique?
A: RLVR uses verifiable rewards to train models on tasks with measurable outcomes, such as solving math problems. This approach has shown significant performance improvements, especially at larger scales.

Q: Can I use Tülu 3 405B for my own projects?
A: Yes! Tülu 3 405B is available on Hugging Face and the Ai2 Playground, making it accessible for researchers and developers to experiment with and integrate into their projects.

Explore the possibilities with Tülu 3 405B—download the model, review the code, and dive into the research paper to see how it can transform your AI workflows.


More information on Tülu 3 405B

Launched
2010-12
Pricing Model
Free
Starting Price
Global Rank
228005
Follow
Month Visit
215.5K
Tech used
Next.js,Gzip,OpenGraph,Webpack,HSTS

Top 5 Countries

42.08%
4.93%
4.41%
4.37%
4.2%
United States China India Malaysia Canada

Traffic Sources

52.25%
36.97%
8.14%
2.32%
0.19%
0.11%
Search Direct Referrals Social Paid Referrals Mail
Tülu 3 405B was manually vetted by our editorial team and was first featured on September 4th 2025.
Aitoolnet Featured banner

Tülu 3 405B Alternatives

Load more Alternatives
  1. Tülu 3 is a leading instruction following model family, offering fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern post-training techniques.

  2. Unlock your coding potential with Replit Code V-1.5 3B. This powerful Causal Language Model offers accurate code suggestions across programming languages.

  3. Alfred-40B-0723 is a finetuned version of Falcon-40B, obtained with Reinforcement Learning from Human Feedback (RLHF).

  4. GLM-4-9B is the open source version of the latest generation pre-training model GLM-4 series launched by Zhipu AI.

  5. OpenBioLLM-8B is an advanced open source language model designed specifically for the biomedical domain.