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🚀 MLSys 2026 Contest - @nvidia Track is LIVE! Registration is now open for the FlashInfer-Bench Challenge! Submit high-performance GPU kernels for cutting-edge LLM architectures on NVIDIA Blackwell GPUs. Three Tracks * MoE (Mixture of Experts) * DSA (Deepseek Sparse Attention) * GDN (Gated Delta Net) Human experts AND AI agents welcome — evaluated separately. Let's see who builds the best kernels! 🤖 🎁 Prizes: Winners take home NVIDIA GPUs and are invited for presentation at MLSys 2026. ⚡ First 50 teams to register get free GPU credits from @modal - huge thanks for the sponsorship @charles_irl ! Whether you're a kernel wizard or building autonomous coding agents, we want to see what you've got. 🔗 Contest details: mlsys26.flashinfer.ai See you at MLSys 2026! 🔥

🚀 MLSys 2026 Contest - @nvidia Track is LIVE! Registration is now open for the FlashInfer-Bench Challenge! Submit high-performance GPU kernels for cutting-edge LLM architectures on NVIDIA Blackwell GPUs. Three Tracks * MoE (Mixture of Experts) * DSA (Deepseek Sparse Attention) * GDN (Gated Delta Net) Human experts AND AI agents welcome — evaluated separately. Let's see who builds the best kernels! 🤖 🎁 Prizes: Winners take home NVIDIA GPUs and are invited for presentation at MLSys 2026. ⚡ First 50 teams to register get free GPU credits from @modal - huge thanks for the sponsorship @charles_irl ! Whether you're a kernel wizard or building autonomous coding agents, we want to see what you've got. 🔗 Contest details: mlsys26.flashinfer.ai See you at MLSys 2026! 🔥

🎉 Congratulations to the FlashInfer team – their technical paper, "FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving," just won best paper at #MLSys2025. 🏆 🙌 We are excited to share that we are now backing FlashInfer – a supporter and contributor to the project. We’ve chosen FlashInfer to release our top LLM inference kernels, including those from TensorRT-LLM, making them easy to integrate into @vllm_project, SGLang (@lmsysorg), and custom inference engines. It started as a collaborative research project at @uwcse, @CarnegieMellon, and OctoAI (acquired by NVIDIA) with the goal of creating a flexible LLM inference kernel library that is engine agnostic, highly optimized, and easy to extend for new techniques such as algorithms for KV cache reuse. It is now a thriving open source project with production deployments and contributions from research and development teams across the AI systems community. Check out FlashInfer today to get started to see our first Blackwell kernels for DeepSeek MLA available now: nvda.ws/4djKdq7 Congratulations again to Zihao Ye and all authors of the MLSys paper -- Lequn Chen, Wuwei Lin, Yineng Zhang, Stephanie Wang, Baris Kasikci, Arvind Krishnamurthy, Vinod Grover, Tianqi Chen, Ruihang Lai. And thank you to all community contributions, we look forward to continuing to grow this project. FlashInfer paper: nvda.ws/4kj2Htc Blackwell MLA kernel: nvda.ws/4jWjLW2

We’re thrilled that FlashInfer won a Best Paper Award at MLSys 2025! 🎉 This wouldn’t have been possible without the community — huge thanks to @lmsysorg’s sglang for deep co-design (which is crtical for inference kernel evolution) and stress-testing over the years, and to @vllm_project for integration support. With continued help from @NVIDIAAIDev , FlashInfer is becoming more stable and faster. Let’s keep building together!

🎉 Congratulations to the FlashInfer team – their technical paper, "FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving," just won best paper at #MLSys2025. 🏆 🙌 We are excited to share that we are now backing FlashInfer – a supporter and contributor to the project. We’ve chosen FlashInfer to release our top LLM inference kernels, including those from TensorRT-LLM, making them easy to integrate into @vllm_project, SGLang (@lmsysorg), and custom inference engines. It started as a collaborative research project at @uwcse, @CarnegieMellon, and OctoAI (acquired by NVIDIA) with the goal of creating a flexible LLM inference kernel library that is engine agnostic, highly optimized, and easy to extend for new techniques such as algorithms for KV cache reuse. It is now a thriving open source project with production deployments and contributions from research and development teams across the AI systems community. Check out FlashInfer today to get started to see our first Blackwell kernels for DeepSeek MLA available now: nvda.ws/4djKdq7 Congratulations again to Zihao Ye and all authors of the MLSys paper -- Lequn Chen, Wuwei Lin, Yineng Zhang, Stephanie Wang, Baris Kasikci, Arvind Krishnamurthy, Vinod Grover, Tianqi Chen. And thank you to all community contributions, we look forward to continuing to grow this project. FlashInfer paper: nvda.ws/4kj2Htc Blackwell MLA kernel: nvda.ws/4jWjLW2

🚀Meet flashinfer.sampling—our sorting-free GPU kernels for lightning-fast #LLM sampling. Our implementation achieves over 50% reduction in sampling time. Blog post: flashinfer.ai/2025/03/10/sam…

We are excite to announce FlashInfer v0.2! Core contributions of this release include: - Block/Vector Sparse (Paged) Attention on FlashAttention-3 - JIT compilation for customized attention variants - Fused Multi-head Latent Attention (MLA) decoding kernel - Lots of bugfix and improvements involving CUDAGraph compatibility, RMSNorm/RoPE numerical issue, etc. blog post: flashinfer.ai/2024/12/16/fla…

📺Day 7: Fictional Characters and Real Change 📺 From Will & Grace to Brazilian telenovelas, widely watched dramas can precipitate dramatic cultural shifts. NGOs promoting public health changes have employed serial dramas to shift cultural ideals and personal decisions. But deliberate efforts don’t always work. For example, director Francois Truffaut noted, "There's no such thing as an anti-war movie.” They don’t hurt military recruitment at all. TRIBAL examines the underlying psychology in the signals sent by works of fiction. This helps us understand related questions involving real people who become cultural heroes and role models. Why did consumers follow Roger Federer’s advice to choose Rolex but not LeBon’s advice to choose Samsung? We’ll see that the keys to why some celebrity endorsements sell and others flop also elucidate the influencer campaigns that are increasingly replacing them. Visit tribalbook.org to learn more. #Media #Brazilian #Telenovelas #PublicHealth #CulturalImpact #CelebrityInfluence #BehavioralChange #SocialCampaigns #CulturalPsychology #TRIBAL

Wanna know whether different LLM providers serve the same LLama 3.1 70B? I sure did! So I ran a quick eval to get some surprising results + open sourced my code 👇 Check out my comparison between @GroqInc @FireworksAI_HQ @OctoAICloud @DeepInfra and @togethercompute