DeepSeek-V3.1: hybrid inference LLM with Think/Non-Think modes, stronger agents, 128K context, strict function calling.
Build advanced AI agents within the biomedical domain using the AI-Q Blueprint and the BioNeMo Virtual Screening Blueprint
Build a data flywheel, with NVIDIA NeMo microservices, that continuously optimizes AI agents for latency and cost — while maintaining accuracy targets.
Streamline evaluation, monitoring, and optimization of AI data flywheel with Weights & Biases.
Orchestrate AI agents for data flywheel with MLRun and NVIDIA NeMo microservices.
Automate and optimize the configuration of radio access network (RAN) parameters using agentic AI and a large language model (LLM)-driven framework.
State-of-the-art open model for reasoning, code, math, and tool calling - suitable for edge agents
Build a custom deep researcher powered by state-of-the-art models that continuously process and synthesize multimodal enterprise data, enabling reasoning, planning, and refinement to generate comprehensive reports.
Natural and expressive voices in multiple languages. For voice agents and brand ambassadors.
Latency-optimized language model excelling in code, math, general knowledge, and instruction-following.
Trace and evaluate AI Agents with Weights & Biases.
Automate voice AI agents with NVIDIA NIM microservices and Pipecat.
Automate research, and generate blogs with AI Agents using LlamaIndex and Llama3.3-70B NIM LLM.
Generate detailed, structured reports on any topic using LangGraph and Llama3.3 70B NIM.
Document your github repositories with AI Agents using CrewAI and Llama3.3 70B NIM.
Ingest massive volumes of live or archived videos and extract insights for summarization and interactive Q&A