tensorrt-llm
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
Install
npx skills add davila7/claude-code-templates@tensorrt-llmRuns in your terminal. Adds the skill globally for Claude Code, Cursor, Codex and others; add -g -y to skip prompts.
What it does
TensorRT-LLM NVIDIA's open-source library for optimizing LLM inference with state-of-the-art performance on NVIDIA GPUs. When to use TensorRT-LLM Use TensorRT-LLM when: - Deploying on NVIDIA GPUs (A100, H100, GB200) - Need maximum throughput (24,000+ tokens/sec on Llama 3) - Require low latency for real-time applications - Working with quantized models (FP8, INT4, FP4) - Scaling across multiple GPUs or nodes Use vLLM instead when: - Need simpler setup and Python-first API - Want PagedAttention without TensorRT compilation - Working with AMD GPUs or non-NVIDIA hardware Use llama.cpp instead…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
View source on GitHubBefore you install
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
Categories
Related skills
- jira
davila7/claude-code-templates
Use when the user mentions Jira issues (e.g., "PROJ-123"), asks about tickets, wants to create/view/update issues, check sprint status, or manage their Jira workflow. Triggers on keywords like "jira", "issue", "ticket", "sprint", "backlog", or issue key patterns.
1.1K installs 31KAI & agentsProductivity - conversation-memory
davila7/claude-code-templates
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
1.0K installs 31KAI & agents - crewai-multi-agent
davila7/claude-code-templates
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
996 installs 31KAI & agents - langchain
davila7/claude-code-templates
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
976 installs 31KReact & Next.jsAI & agentsGit & GitHub - modal-serverless-gpu
davila7/claude-code-templates
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
972 installs 31KDeploy & DevOpsDataPython - context7-auto-research
davila7/claude-code-templates
Automatically fetch latest library/framework documentation for Claude Code via Context7 API
736 installs 31KReact & Next.jsDocumentationResearch