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

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

Tuning the LangChain Deep Agents harness for NVIDIA Nemotron 3 Ultra delivers leading performance and faster task completion on an open stack that enterprises can run, customize and control. 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. 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. 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. 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. LangChain's agent engineering platform has more than 200 million monthly downloads. By tuning its Deep Agents harness specifically for NVIDIA Nemotron 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. "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." Abridge, Amdocs and Box are embedding specialized agents directly into their platforms and global systems integrator EY 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. 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. Harness Engineering, Not Fine-Tuning LangChain's team ran Nemotron 3 Ultra against its public Deep Agents benchmark suite, then analyzed the deep agent's execution traces to find exactly where it lost points. Instead of retraining the model, the team tuned the harness around it -- adjusting system prompts, tool descriptions and middleware. Every developer using LangChain Deep Agents with Nemotron 3 Ultra can put this to work today -- the tuned profile is available directly through LangChain. An Open Stack Built to Own NVIDIA NemoClaw for LangChain Deep Agents is the open reference blueprint that packages this work for enterprises building their own specialized AI -- systems of models, tools and runtime -- tuned for their own workflows. It combines LangChain Deep Agents Code, tuned for Nemotron 3 Ultra, with the NVIDIA OpenShell secure runtime for executing agent actions safely. 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. 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. NemoClaw for LangChain Deep Agents and the tuned Nemotron 3 Ultra model profile are available now. Developers can pull the tuned Deep Agents harness directly from LangChain, or use the NemoClaw for LangChain Deep Agents blueprint as a starting point for building specialized agents from scratch. How to Get Started LangChain developers can access Nemotron 3 Ultra on Baseten, Crusoe Cloud, DeepInfra, Fireworks, Nebius and Together AI platforms, giving them a direct, hosted path to the tuned harness in production. EY can help enterprises start building their own specialized agents today, using this open software stack. Learn more about NVIDIA NemoClaw for LangChain Deep Agents and NVIDIA Nemotron. Stay up to date on agentic AI, NVIDIA Nemotron and more by subscribing to NVIDIA news, joining the community, and following NVIDIA AI on LinkedIn, Instagram, X and Facebook.

LangChain And NVIDIA Launch NemoClaw Deep Agents Blueprint For Enterprise Agents

LangChain announced the NemoClaw for LangChain Deep Agents blueprint, developed with NVIDIA to help enterprises build, evaluate, and deploy advanced open agent systems. The new blueprint combines LangChain Deep Agents Code, NVIDIA Nemotron 3 Ultra, and NVIDIA OpenShell runtime so teams can customize agents for their workloads, deploy them securely, and run them at lower cost. LangChain's evaluation benchmarks show that enterprises can now get top-performing agents from an open agent stack. In LangChain's agent eval suite, NVIDIA Nemotron 3 Ultra evaluated with LangChain Deep Agents achieved an aggregate score of 0.86 at a cost of $4.48. The next closest performing model cost $43.48, making Nemotron 3 Ultra roughly 10x lower inference cost on this benchmark. The results reflect harness customizations made for Nemotron 3 Ultra. LangChain tuned how the agent uses tools, manages context, and evaluates intermediate steps with Deep Agents. Lower inference costs also make it practical to run and evaluate more specialized agents in production. Teams can create agents for specific domains, use evals and traces to measure performance, and adapt the harness as their workflows change. The NemoClaw for LangChain Deep Agents blueprint brings together three components essential for building agents for the enterprise: NVIDIA Nemotron 3 Ultra provides the open-weight model layer for teams that want to customize model behavior for their domains while improving agent performance and lowering cost. LangChain Deep Agents provides the harness layer for long-running agents, including planning, tool use, memory, and task execution. The Blueprint includes a Deep Agents harness profile is tuned for Nemotron 3 Ultra. NVIDIA OpenShell provides the runtime layer for secure, governed deployment, helping teams control how agents interact with tools, systems, and data. Together, these components give teams a tuned agent system that can be deployed, measured, governed, and improved in production. The announcement is supported by partners across the AI infrastructure and enterprise ecosystem, including EY, who is building an implementation practice around the software stack, and Baseten, Fireworks, Nebius, Crusoe, DeepInfra, and Together AI. These partners help enterprises serve Nemotron models in production and adapt the blueprint for business critical applications. The NemoClaw for LangChain Deep Agents Blueprint is available now. Enterprises can access the blueprint to evaluate the stack for their own workloads.