Introducing Qwen3! We release and open-weight Qwen3, our latest large language models, including 2 MoE models and 6 dense models, ranging from 0.6B to 235B. Our flagship model, Qwen3-235B-A22B, achieves competitive results in benchmark evaluations of coding, math, general

Llama-Nemotron-v1 technical report is now available on arxiv arxiv.org/pdf/2505.00949…

📣 Introducing AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning (RL) Starting from the SFT model DeepSeek-R1-Distill-Qwen-14B, our AceReason-Nemotron-14B achieves substantial improvements in pass@1 accuracy on key benchmarks through RL: AIME

with just math-RL, AceReason-Nemotron-14B surpass DeepCoder-14B on LiveCodeBench v5. we then did code-RL and found training becomes so much easier

Lots of good analysis in here!

Nvidia just dropped AceReason-Nemotron on Hugging Face Advancing Math and Code Reasoning through Reinforcement Learning

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Pass@1024 results of our RL model (AceReason-Nemotron-7B) and its starting SFT model (DeepSeek-R1-Distill-Qwen-7B) on LiveCodeBench-v6, which features a large answer space and high-quality test cases that are difficult to solve through 'guessing', even with extensive sampling.

New reasoning Nemotron-H models are now publicly available. These models are based on hybrid architecture! 47B and 8B in BF16 and FP8. Blogpost: developer.nvidia.com/blog/nemotron-… Weights: huggingface.co/collections/nv…

Cosmos-Reason1 has exciting updates 💡 Now it understands physical reality — judging videos as real or fake! Check out the resources👇 Paper: arxiv.org/abs/2503.15558 Huggingface: huggingface.co/nvidia/Cosmos-… Code: github.com/nvidia-cosmos/… Project page: research.nvidia.com/labs/dir/cosmo… (1/n)

If they can handcuff a U.S. Senator for asking a question, imagine what they will do to you.

📢We conduct a systematic study to demystify the synergy between SFT and RL for reasoning models. The result? We trained a 7B model - AceReason-Nemotron-1.1, significantly improved from version 1.0 on math and coding benchmarks. ✅AIME2025 (math): 53.6% -> 64.8% ✅LiveCodeBench

Introducing AceReason-Nemotron 1.1 Our previous release, AceReason-Nemotron-1.0, introduced a stage-wise RL recipe that was applied sequentially to math-only and code-only prompts, demonstrating both high efficiency and strong effectiveness. Here, we systematically investigate

Checkout our detailed study on advancing math and code reasoning using SFT and RL.

Our released evaluation toolkit can reproduce our AceReason-Nemotron models numbers (see below): AceReason-Nemotron-1.0-7B: LiveCodeBench (Avg@8): * [05/23-05/24]: 72.0; [06/24-01/25]: 54.2 * release set v5: 51.2; release set v6: 44.4 AIME (Avg@64): * AIME'24: 68.6; AIME'25:

🤯 Audio Flamingo 3 is out already... and that's before Audio Flamingo 2 makes its debut at ICML on Wednesday, July 16 at 4:30 p.m.! These benchmark results are insane! arxiv.org/abs/2507.08128