NVIDIA AI Developer

Love seeing these new 🦞 homes - share your setup and we'll start posting them.

In @kxsystems recent blog, they detail how native GPU acceleration speeds up analytic and AI workloads for multimodal data by up to 25x. Acceleration is now built into KDB-X through NVIDIA cuVS and cuDF, enabling faster time series analytics, vector, and AI workloads in a single platform. kx.com/blog/kdb-x-is-…

@IanAndrewsDC @openclaw @nvidia 💚

MY @openclaw 🦞 loves the new @nvidia Spark ⚡️models deploying now 😀

OpenShell v0.0.28 🐳 Docker skeleton: openshell-prover + Z3 🧩 unified Z3 support across dev + Docker 🖥️ libkrun VM build fixes (x86_64, PATH) 🧪 sandbox tests for non-root CI Prover tooling is now integrated across dev and container environments. github.com/NVIDIA/OpenShe…

@ollama 🙌

MiniMax M2.7 is available on Ollama's cloud, and is licensed for commercial usage. Use it with OpenClaw: ollama launch openclaw --model minimax-m2.7:cloud Coding agents, such as Claude: ollama launch claude --model minimax-m2.7:cloud Chat with the model: ollama run minimax-m2.7:cloud

@vllm_project @MiniMax_AI 🙌

🎉 Congrats to @MiniMax_AI on this release. Day-0 support for MiniMax M2.7 in vLLM! 🤖 Agentic-first design. Multi-agent orchestration ("Agent Teams") and complex skill management 💻 Strong coding. Production debugging, log analysis, and code security 📄 Office automation. Proficient in document editing across Word, Excel, and PowerPoint Get started 👇 📖 docs.vllm.ai/projects/recip…

@lmsysorg @MiniMax_AI 🙌

🎉 Congrats on releasing MiniMax M2.7 from @MiniMax_AI, the first model deeply participating in its own evolution. Day-0 support is now live in SGLang! 🤖 Model self-evolution: autonomously optimized a scaffold over 100+ rounds with 30% performance gain 🏆 MLE Bench Lite: 66.6% medal rate, #2 overall (behind Opus 4.6 & GPT-5.4) 🔧 SWE: SWE-Pro 56.22%, SWE Multilingual 76.5, Multi SWE Bench 52.7 📊 Professional work: ELO 1495 on GDPval-AA (highest open-source), MM Claw 62.7% 👥 Native Agent Teams for stable multi-agent collaboration Optimized by @nvidia with SGLang, and you can try it on NVIDIA NIM Endpoint: build.nvidia.com Cookbook: cookbook.sglang.io/autoregressive… Try it now with SGLang!

🎉Congratulations to the @MiniMax_AI team on the launch of MiniMax M2.7! MiniMax M2.7 is now available with NVIDIA GPU accelerated endpoints ready to try out with claws including NemoClaw and @OpenClaw. 🦞 📝Get started with our technical guide: developer.nvidia.com/blog/minimax-m… and see how you can begin experimenting for free at build.nvidia.com/minimaxai/mini…. What will you build this weekend? Share in comments. 👇

@MiniMax_AI 🙌

We're delighted to announce that MiniMax M2.7 is now officially open source. With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%). You can find it on Hugging Face now. Enjoy!🤗 huggingface：huggingface.co/MiniMaxAI/Mini… Blog: minimax.io/news/minimax-m… MiniMax API: platform.minimax.io

The conversation and learnings don't stop . . . Explore the full playlist of our NVIDIA higher education sessions to gain insights and practical strategies to apply across teaching, learning, and academic innovation today. 📺 Watch #NVIDIAGTC sessions on-demand: nvidia.com/en-us/on-deman…

Figure and Hark just took an entire data center of NVIDIA B200s - every rack in the building Figure will be using these to predict physics and Hark will train next generation multi-modal models

@adcock_brett @Figure_robot @hark_labs 🙌

OpenShell v0.0.26 🖥️ openshell-vm: libkrun-based microVM gateway 📄 docs on Fern 🧩 modular gRPC server refactor 🧪 dedicated GPU CI workflows 🧹 docs structure + nav cleanup Run agents in isolated microVMs, not just processes. github.com/NVIDIA/OpenShe…

Assigning mechanical properties to 3D objects for physics simulation has been slow and manual — until now. VoMP is the first feed-forward model to predict volumetric material properties for any 3D representation, and the code + models are now open-source. ⬇️

@IanAndrewsDC Let's go!

New toy 😀

✨ New livestream: How to implement reinforcement learning effectively? @PrimeIntellect & @UnslothAI join us for a deep-dive into RL with Nemotron — covering GRPO, RLVR, and building memory-efficient RL pipelines for domain-specific training. 🗓️ Apr 14 | 11am PT → nvda.ws/3Q1GWEh Bring your questions for the live Q&A, and share in comments.

Introducing DWDP = “Distributed Weight Data Parallelism” for MoE LLM inference using NVL72-based clusters from #NVIDIAResearch. Keep data parallel, offload MoE experts across GPUs, fetch on demand with P2P copies, and drop layer‑wise collectives to accelerate your parallel LLM inference projects. Shows gain of ~9–11% higher output TPS/GPU on DeepSeek‑R1 at similar TPS/user, with bigger wins under imbalanced traffic. 📗 arxiv.org/abs/2604.01621

@aleks_todo @steipete @openclaw he's a man on a mission!

@NVIDIAAIDev @steipete @openclaw du bist überall aber du bist trotzdem locked in af, wie machst du das?? Hast du'n clone oder laufen die claws auf spud?

Green and red have never looked so good. 💚🦞 NVIDIA CEO Jensen Huang surprises our panel guests at the #NVIDIAGTC keynote pregame. Watch the replay to hear the full conversation with @steipete, creator of @OpenClaw, on their partnership and the future of intelligent AI model. 🔗 youtube.com/live/RTmSrIFZa…

DGX Spark Live: cuTile Kernels from Spark to Cloud x.com/i/broadcasts/1…

@TheEcomNomad beautiful - keep us posted

everyone said buying 1 DGX Spark sight unseen from 2,400 miles away was crazy so naturally i got a second one that's 2 personal supercomputers on my desk. 2 petaFLOPS. 256GB of unified memory. linked together running models that needed a data center last year. this is not normal behavior and i'm aware of that i might need a third