← Back
NVIDIA Blog

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

4 min read
#agents#langchain#nvidia#inference
NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness
Level:Advanced
For:AI Engineers
TL;DR

NVIDIA Nemotron 3 Ultra has achieved benchmark-leading performance with LangChain Deep Agents harness, offering leading performance at a lower cost than top closed models. The LangChain team tuned its Deep Agents harness for NVIDIA Nemotron 3 Ultra, achieving the highest accuracy among open models and completing more tasks at higher throughput while running at 10x lower inference cost per run. This was achieved without retraining the model, but rather by engineering the environment around it. The practical implication for engineers building AI systems is that they can now run evaluations continuously, experiment faster, and build specialized agents across more of their business at a lower cost.

⚡ Key Takeaways

  • NVIDIA Nemotron 3 Ultra achieved the highest accuracy among open models on the LangChain Deep Agents benchmark.
  • The tuned Deep Agents harness for NVIDIA Nemotron 3 Ultra runs at 10x lower inference cost per run than leading closed models.
  • The NVIDIA NemoClaw blueprint for LangChain Deep Agents provides an open reference for enterprises to build their own specialized AI systems.
  • The LangChain Deep Agents code is combined with the NVIDIA OpenShell secure runtime for executing agent actions safely.
  • The open model, open harness, and open secure runtime allow enterprises to own the full stack, customize it, and run it anywhere.
💡 Why It Matters

The achievement of NVIDIA Nemotron 3 Ultra with LangChain Deep Agents harness has significant implications for engineers building production AI systems, as it provides a cost-effective and high-performance solution for building specialized agents. This can enable businesses to automate more tasks, improve efficiency, and reduce costs.

✅ Practical Steps

  1. Use the tuned Nemotron 3 Ultra model profile available through LangChain to improve the performance of Deep Agents.
  2. Implement the NVIDIA NemoClaw blueprint for LangChain Deep Agents to build specialized AI systems.
  3. Combine LangChain Deep Agents code with the NVIDIA OpenShell secure runtime for secure execution of agent actions.

Want the full story? Read the original article.

Read on NVIDIA Blog

More like this

57% of enterprises have watched AI agents be confidently wrong. The fix is an agentic context layer, but who has one?

VentureBeat AI#agents

Choosing the Right AI Agent Memory Strategy: A Decision-Tree Approach

Machine Learning Mastery#agents

Fine-tune NVIDIA Nemotron 3 models with Amazon SageMaker AI serverless model customization

AWS ML Blog#llm

The Pulse: Interesting AI coding stats from Cursor

Pragmatic Engineer#vibe coding

EXPLORE AI NEWS

Daily hand-picked stories on LLMs, RAG, agents and production AI — curated for engineers who ship.

BROWSE NEWS

GET THE WEEKLY DIGEST

Join engineers getting the Monday signal-over-noise AI breakdown. No spam, unsubscribe anytime.

LEARN AI ENGINEERING

Curated courses, research papers, repos and tutorials built for engineers leveling up in AI.

START LEARNING