LTX-2 vs ray
LTX-2 and ray share 14 technologies: Google, Rich, sentencepiece, torch, triton, safetensors, torchvision, bitsandbytes, peft, imageio, torchcodec, pillow, imageio-ffmpeg, and Pydantic. Both are written in Python.
What they share and what sets them apart
Lightricks
LTX-2
Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.
Python10.2kRead on November 13, 2026, at commit f0f2f86What is LTX-2 built with?Only in LTX-2
OpenAI- NVIDIA
accelerate
torchaudio
- optimum-quanto
av
- pillow-heif
In common
ray-project
ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Python44.3kRead on November 13, 2026, at commit de4c576What is ray built with?Only in ray
- FastAPI
- aimrecords
- aimrocks
- amqp
- array-record
- arro3-core
- async-lru
- azure-common
- azure-datalake-store
- azure-storage-blob
confluent-kafka
- delta-kernel-rust-sharing-wrapper
- diskcache
expiringdict
- feather-format
- gitdb
google-cloud-core
h5py
- huey
jupyter-cache
kombu
- partd
petastorm
pickleshare
- py-partiql-parser
- pylance
- pymongo
- qpd
- s3torchconnectorclient
- s3transfer
- semidbm
- sqlitedict
taskiq
tensorboard-data-server
- zict
pyarrow
mcap
- aioboto3
- MongoDB
- Redis
- adlfs
pyiceberg
- smart-open
clickhouse-connect
daft
deltalake
- gcsfs
lance-namespace
- obstore
- Celery
delta-sharing
- fastavro
hudi
- pyzmq
- s3fs
- s3torchconnector
- taskiq-redis
zarr
- Hugging Face
- Google Cloud Storage
- Kafka
- Databricks
- adagio
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
pygame
pymars
werkzeug
- Ray
starlette
- AIOHTTP
pyspark
- Lightning
raydp
- anyio
tornado
uvicorn
- React
react-router-dom
- accessible-pygments
- alabaster
- cycler
fonttools
jupyterlab-pygments
pydata-sphinx-theme
- soupsieve
sphinx-design
- tinycss2
- aim-ui
- alive-progress
bokeh
contourpy
- glfw
halo
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
prompt-toolkit
pyglet
pyopengl
- spinners
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
- pydot
- alembic
peewee
sqlglot
- adal
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
- gcs-oauth2-boto-plugin
google-auth-oauthlib
- google-oauth
- google-reauth
- id
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
- pyu2f
requests-oauthlib
- cryptography
google-auth-httplib2
- aws-requests-auth
- albucore
- autograd
ax-platform
- bayesian-optimization
botorch
- cma
cmdstanpy
- crcmod
cupy-cuda100
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
- fbgemm-gpu
- gpytorch
gradio-client
- gym
jaxlib
- labmaze
- LangChain
- lightning-utilities
- linear-operator
- llvmlite
lm-eval
- minigrid
- ml-dtypes
- moocore
mosaicml
nltk
- ONNX
onnx-ir
- onnxruntime
onnxscript
openai-whisper
- opt-einsum
optax
- orbax-checkpoint
prophet
pymoo
pyro-ppl
- pytorch-ranger
rouge-score
- sacrebleu
scikit-image
skops
stanio
statsforecast
tf-keras
- tiktoken
timm
tokenizers
- torch-geometric
- torch-optimizer
- torch-scatter
- torch-sparse
torchtext
- yahp
- gymnasium
- transformers
- TensorFlow
jax
- xgboost
lightgbm
- scikit-learn
- MLflow
- datasets
- pytorch-lightning
- comet-ml
- dm-env
flax
- Keras
- torchmetrics
- aim
ale-py
configspace
deepspeed
diffusers
- dm-control
- hpbandster
- hyperopt
- nevergrad
- open-spiel
- Optuna
tensorflow-probability
- zoopt
- bleach
- defusedxml
et-xmlfile
- imagesize
- jsonlines
- linkify-it-py
lxml
- mako
- markdown
markdown-it-py
markupsafe
- mdit-py-plugins
- mdurl
mistune
- moviepy
myst-parser
- nbconvert
- nh3
- openpyxl
- pandocfilters
- pytablewriter
- readme-renderer
ruamel-yaml
ruamel-yaml-clib
- strictyaml
- tinyscaler
webencodings
- xlrd
- xmltodict
- docutils
- jinja2
- beautifulsoup4
- decord
- nbformat
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-path
- jsonschema-specifications
- openapi-spec-validator
- pathvalidate
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- typepy
- validators
- jsonschema
- aiobotocore
- applicationinsights
- aws-sam-translator
aws-xray-sdk
- azure-cli-core
- azure-cli-telemetry
- azure-core
- azure-mgmt-compute
- azure-mgmt-core
- azure-mgmt-network
- azure-mgmt-resource
- azure-mgmt-resource-deployments
- boto
- cloud-tpu-diagnostics
- colorlog
- execnet
google-cloud-audit-log
- Gunicorn
- log-symbols
- ml-goodput-measurement
- msrestazure
- opencensus-context
opentelemetry-instrumentation
opentelemetry-instrumentation-asgi
opentelemetry-semantic-conventions
opentelemetry-util-http
- python-json-logger
- supervisor
psutil
- boto3
- botocore
prometheus-client
- pybuildkite
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- ray-haproxy
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
Side by side
LTX-2ray
SizeLines written by people and agents, without generated ones; code files, without tests.
LTX-281,590 lines written364 code files
ray1,566,356 lines written2,810 code files
Who writes itA commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
LTX-20% of its commits signed by AI
ray3.7% of its commits signed by AIWith Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex
ActivityFrom GitHub and its history, on the day SeeRepo read it.
LTX-2Last push November 12, 202636 commits10,227 stars
rayLast push November 13, 202632,468 commits44,282 stars
TestsThe files that test the code, and the share of code files a test imports.
LTX-20 test files
ray2,208 test files9.4% of its code files have a test that imports them
Frequently asked questions
Which is bigger, LTX-2 or ray?
ray, with 1,566,356 lines written; LTX-2 has 81,590.
The proof: ray-project/ray's code at commit de4c576
Which has more GitHub stars, LTX-2 or ray?
ray, with 44,282 stars; LTX-2 has 10,227.
The proof: ray-project/ray on GitHub
Which has more tests, LTX-2 or ray?
ray, with 2,208 test files.
The proof: ray-project/ray's code at commit de4c576
Which was updated more recently, LTX-2 or ray?
ray: its last push was on November 13, 2026, and LTX-2's on November 12, 2026.
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, LTX-2 or ray?
ray: an AI signed 3.7% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex.
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