NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness

<div id="bsf_rt_marker"></div><p><span style="font-weight: 400;">NVIDIA Nemotron 3 Ultra is offering leading performance at lower cost than top closed models with the largest and most widely adopted AI agent orchestration platform. </span></p> <p><span style="font-weight: 400;">LangChain tuned its Deep Agents harness for NVIDIA Nemotron 3 Ultra, achieving the highest accuracy among open models, while completing more tasks at higher throughput and running at 10x lower inference cost per run than leading closed models. </span></p> <p><span style="font-weight: 400;">Measured against LangChain’s Deep Agents benchmark, Nemotron 3 Ultra also achieved business task parity with the highest-scoring closed models. No model retraining was required. Every gain came from engineering the environment around the model, not the model itself. </span></p> <p><span style="font-weight: 400;">At a tenth of the cost, teams harnessing NVIDIA Nemotron 3 Ultra can run evaluations continuously, experiment faster and build specialized agents across more of their business. </span></p> <p><span style="font-weight: 400;">LangChain’s agent engineering platform has more than 200 million monthly downloads. By tuning its Deep Agents harness specifically for </span><a target="_blank" href="https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/"><span style="font-weight: 400;">NVIDIA Nemotron</span></a><span style="font-weight: 400;"> 3 Ultra, it allows for high-performing agents that complete more tasks, run faster and give enterprises a fully open stack they can customize, own and run anywhere.</span></p> <p><span style="font-weight: 400;">“The way to build better agents is to keep improving the system around the model,” said Harrison Chase, cofounder and CEO of LangChain. “Memory, tool use, evaluation and model behavior compound when teams can tune them together. Our work with NVIDIA shows that enterprises can get strong performance from an open stack while keeping control over the agent systems they are building.”</span></p> <p><span style="font-weight: 400;">Abridge,</span> <span style="font-weight: 400;">Amdocs</span><span style="font-weight: 400;"> and </span><span style="font-weight: 400;">Box</span><span style="font-weight: 400;"> are embedding specialized agents directly into their platforms and global systems integrator </span><span style="font-weight: 400;">EY</span><span style="font-weight: 400;"> is expanding its NVIDIA implementation capabilities around NVIDIA NemoClaw blueprints for LangChain Deep Agents, helping clients customize, evaluate and govern specialized agents across high-value workflows. </span></p> <p><span style="font-weight: 400;">NVIDIA founder and CEO Jensen Huang recently sat down with Chase to discuss why the last six months have seen a leap in useful AI for enterprises.</span></p> <p><iframe title="Jensen Huang: Why companies need open agent systems" width="1200" height="675" src="https://www.youtube.com/embed/Yy3JH6dDugc?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe></p> <h2>Harness Engineering, Not Fine-Tuning</h2> <p><span style="font-weight: 400;">LangChain’s team ran Nemotron 3 Ultra against its public Deep Agents benchmark suite, then analyzed the </span><a target="_blank" href="https://www.nvidia.com/en-us/glossary/deep-agents/"><span style="font-weight: 400;">deep agent’s</span></a><span style="font-weight: 400;"> execution traces to find exactly where it lost points. Instead of retraining the model, the team <a target="_blank" href="https://developer.nvidia.com/blog/create-a-langchain-deep-agents-harness-profile-for-nvidia-nemotron-3-ultra-to-improve-performance/">tuned the harness</a> around it — adjusting system prompts, tool descriptions and middleware.</span></p> <p><span style="font-weight: 400;">Every developer using LangChain Deep Agents with Nemotron 3 Ultra can put this to work today — the tuned profile is available directly through LangChain.</span></p> <h2>An Open Stack Built to Own</h2> <p><span style="font-weight: 400;">NVIDIA NemoClaw for LangChain Deep Agents is the open reference blueprint that packages this work for enterprises building their own </span><a target="_blank" href="https://www.nvidia.com/en-us/glossary/specialized-ai/"><span style="font-weight: 400;">specialized AI</span></a><span style="font-weight: 400;"> — </span><a target="_blank" href="https://www.nvidia.com/en-us/glossary/multi-agent-systems/"><span style="font-weight: 400;">systems of models</span></a><span style="font-weight: 400;">, tools and runtime — tuned for their own workflows. It combines LangChain Deep Agents Code, tuned for Nemotron 3 Ultra, with the </span><a target="_blank" href="https://build.nvidia.com/openshell"><span style="font-weight: 400;">NVIDIA OpenShell</span></a><span style="font-weight: 400;"> secure runtime for executing agent actions safely.</span></p> <p><span style="font-weight: 400;">An open model, an open harness and an open secure runtime means enterprises own the full stack, end to end. They can customize it around the expertise that sets their business apart, keep improving it and run it anywhere — their own infrastructure, their own cloud, their own governance. </span></p> <p><span style="font-weight: 400;">That distinction matters more as agents take on higher-stakes work. The shift from AI assistants that answer questions to agents that take action inside core systems changes what businesses get from their AI. </span></p> <p><span style="font-weight: 400;">NemoClaw for LangChain Deep Agents and the tuned Nemotron 3 Ultra model profile are available </span><a target="_blank" href="https://docs.langchain.com/oss/python/deepagents/code/overview"><span style="font-weight: 400;">now</span></a><span style="font-weight: 400;">. Developers can pull the tuned Deep Agents harness directly from LangChain, or use the </span><a target="_blank" href="https://build.nvidia.com/nvidia/nemoclaw-for-langchain-deep-agents-code/"><span style="font-weight: 400;">NemoClaw for LangChain</span></a><span style="font-weight: 400;"> Deep Agents blueprint as a starting point for building specialized agents from scratch. </span></p> <h2>How to Get Started</h2> <p><span style="font-weight: 400;">LangChain developers can access Nemotron 3 Ultra on</span> <a target="_blank" href="https://www.baseten.co/blog/nvidia-nemotron-3-ultra-and-langchain-deep-agents-on-baseten"><span style="font-weight: 400;">Baseten</span><span style="font-weight: 400;">,</span></a> <a target="_blank" href="https://www.crusoe.ai/cloud/managed-inference"><span style="font-weight: 400;">Crusoe Cloud</span></a><span style="font-weight: 400;">, </span><a target="_blank" href="https://deepinfra.com/blog/nvidia-nemotron-3-ultra-langchain-deep-agents"><span style="font-weight: 400;">DeepInfra</span><span style="font-weight: 400;">, </span></a><a target="_blank" href="https://fireworks.ai/models/fireworks/nemotron-3-ultra-nvfp4?utm_term=nemotron%203%20ultra&amp;utm_campaign=SEM_Non_Brand&amp;utm_source=adwords&amp;utm_medium=ppc&amp;utm_id=23966119562&amp;hsa_acc=6824341280&amp;hsa_cam=23966119562&amp;hsa_grp=194972178142&amp;hsa_ad=813772870557&amp;hsa_src=g&amp;hsa_tgt=kwd-2542408021127&amp;hsa_kw=nemotron%203%20ultra&amp;hsa_mt=p&amp;hsa_net=adwords&amp;hsa_ver=3&amp;gad_source=1&amp;gad_campaignid=23966119562&amp;gbraid=0AAAAA-vkpDMHe2p_mlpf0kNvWazZouP_z&amp;gclid=CjwKCAjwx7LSBhB3EiwAjcodxGaGsV2DVKTGCc5iGx4leadXuyXl4uK_Z9rPKJzlJnFsi-M_UlCGixoCv0YQAvD_BwE"><span style="font-weight: 400;">Fireworks</span><span style="font-weight: 400;">,</span></a> <a target="_blank" href="https://dev.nebius.com/blueprints?utm_source=nvidia&amp;utm_medium=partner-blog&amp;utm_campaign=langchain-nemoclaw-launch-2026-07&amp;utm_content=cta-deploy"><span style="font-weight: 400;">Nebius</span></a><span style="font-weight: 400;"> and </span><a target="_blank" href="https://togetherai.link/IyR8AH2"><span style="font-weight: 400;">Together AI</span></a> <span style="font-weight: 400;"> platforms, giving them a direct, hosted path to the tuned harness in production. </span></p> <p><span style="font-weight: 400;">EY</span><span style="font-weight: 400;"> can help enterprises start building their own specialized agents today, using this open software stack.  </span></p> <p><span style="font-weight: 400;"><a target="_blank" href="https://www.prnewswire.com/news-releases/langchain-and-nvidia-launch-nemoclaw-deep-agents-blueprint-for-enterprise-agents-302820446.html">Learn more</a> about NVIDIA NemoClaw for LangChain Deep Agents and NVIDIA Nemotron. </span></p> <p><i><span style="font-weight: 400;">Stay up to date on agentic AI, </span></i><a target="_blank" href="https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/"><i><span style="font-weight: 400;">NVIDIA Nemotron</span></i></a><i><span style="font-weight: 400;"> and more by subscribing to </span></i><a target="_blank" href="https://www.nvidia.com/en-us/executive-insights/generative-ai-tools/?modal=stay-inf"><i><span style="font-weight: 400;">NVIDIA news</span></i></a><i><span style="font-weight: 400;">,</span></i><a target="_blank" href="https://developer.nvidia.com/community"><i><span style="font-weight: 400;"> joining the community</span></i></a><i><span style="font-weight: 400;">, and following NVIDIA AI on </span></i><a target="_blank" href="https://www.linkedin.com/showcase/nvidia-ai/posts/?feedView=all"><i><span style="font-weight: 400;">LinkedIn</span></i></a><i><span style="font-weight: 400;">, </span></i><a target="_blank" href="https://www.instagram.com/nvidiaai/?hl=en"><i><span style="font-weight: 400;">Instagram</span></i></a><i><span style="font-weight: 400;">, </span></i><a target="_blank" href="https://x.com/NVIDIAAIDev"><i><span style="font-weight: 400;">X</span></i></a><i><span style="font-weight: 400;"> and </span></i><a target="_blank" href="https://www.facebook.com/NVIDIAAI"><i><span style="font-weight: 400;">Facebook</span></i></a><i><span style="font-weight: 400;">.  </span></i></p> <p><i><span style="font-weight: 400;">Explore </span></i><a target="_blank" href="https://youtube.com/playlist?list=PL5B692fm6--vdRKB14FImVi7MTJ77zjn4&amp;feature=shared"><i><span style="font-weight: 400;">self-paced video tutorials and livestreams</span></i></a><i><span style="font-weight: 400;">.</span></i></p> <p>&nbsp;</p>