TensorRT-LLM vs llama_index
TensorRT-LLM and llama_index share 25 technologies: pyzmq, OpenAI, anyio, starlette, Rich, matplotlib, optimum, sentencepiece, tiktoken, torch, transformers, einops, datasets, MCP, tritonclient, peft, pillow, jinja2, Pydantic, jsonschema, opentelemetry-api, psutil, prometheus-client, boto3, and OpenTelemetry. Both are written in Python.
What they share and what sets them apart
TensorRT-LLM
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
Python15kRead on November 8, 2026, at commit b433473What is TensorRT-LLM built with?Only in TensorRT-LLM
- FastAPI
- blobfile
h5py
uvicorn
- Plotly
accelerate
apache-tvm-ffi
- cuda-python
flash-linear-attention
flashinfer-python
- NVIDIA
nvidia-cudnn-frontend
openai-codex
- openai-harmony
- quack-kernels
- rouge
rouge-score
- torch-c-dlpack-ext
torchao
- triton
diffusers
safetensors
torchvision
- flash-attn
xgrammar
librosa
- mistral-common
partial-json-parser
evaluate
- llguidance
lm-eval
- jsonlines
- mako
msgspec
- opentelemetry-semantic-conventions-ai
- opentelemetry-sdk
- prometheus-fastapi-instrumentator
In common
llama_index
LlamaIndex is the document processing platform for AI
Python52.8kRead on November 5, 2026, at commit 444fdf0What is llama_index built with?Only in llama_index
- aiomysql
- aiosqlite
- async-lru
- asyncpg
- azure-search-documents
- azure-storage-blob
- ibm-db
- pgvecto-rs
pgvector
psycopg
psycopg2-binary
- Redis
weaviate-client
pyarrow
lancedb
oracledb
- DuckDB
- pymilvus
- SQLite
- tablestore
chromadb
falkordb
- MySQL
pinecone
clickhouse-connect
- gcsfs
pyiceberg
pymochow
- pymysql
- pyobvector
- s3fs
- tcvectordb
typesense
- ElevenLabs
- graphql-core
tornado
- AIOHTTP
- Ray
- soupsieve
- tinycss2
- ipywidgets
- matplotlib-inline
prompt-toolkit
- SQLAlchemy
- argon2-cffi
- azure-identity
google-auth-httplib2
google-auth-oauthlib
- cryptography
- pyjwt
- msal
firecrawl-py
- guardrails-ai
llama-index-core
- mem0ai
opencv-python
- PaddlePaddle
- tavily-python
- ibm-watsonx-ai
cohere
- LangChain
sentence-transformers
dashscope
- fastembed
- flagembedding
nltk
litellm
- ModelScope
- Ollama
- openvino
- scikit-learn
- vLLM
- exa-py
- flashrank
- hnswlib
langfuse
mlx
- mlx-lm
nomic
- paddleocr
presidio-analyzer
tokenizers
- beautifulsoup4
- bleach
markupsafe
mistune
- nbformat
- newspaper3k
- xlrd
- bs4
- html2text
unstructured
- defusedxml
lxml
pymupdf
- filetype
- docx2txt
- markdownify
docling
- lxml-html-clean
- markitdown
- nbconvert
- pdf2image
- pdfplumber
pypdf
pypdf2
tinytag
- youtube-transcript-api
- jsonschema-specifications
marshmallow
- referencing
- rfc3339-validator
docling-core
- annotated-types
- pydantic-core
opentelemetry-semantic-conventions
- python-json-logger
- docker
- Alibaba Cloud
Side by side
Frequently asked questions
Which is bigger, TensorRT-LLM or llama_index?
The proof: NVIDIA/TensorRT-LLM's code at commit b433473
Which has more GitHub stars, TensorRT-LLM or llama_index?
The proof: run-llama/llama_index on GitHub
Which has more tests, TensorRT-LLM or llama_index?
The proof: NVIDIA/TensorRT-LLM's code at commit b433473
Which was updated more recently, TensorRT-LLM or llama_index?
The proof: NVIDIA/TensorRT-LLM's commits on GitHub
Which has more commits signed by AI, TensorRT-LLM or llama_index?
The proof: the commits each tool signed in NVIDIA/TensorRT-LLM
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