Source: https://seerepo.com/compare/ray-project/ray/vs/RVC-Boss/GPT-SoVITS
Markdown source: https://seerepo.com/compare/ray-project/ray/vs/RVC-Boss/GPT-SoVITS.md
Description: ray and GPT-SoVITS share 20 technologies: FastAPI, Hugging Face, starlette, Gradio, matplotlib, einops, onnxruntime, openai-whisper, peft, safetensors, sentencepiece, tiktoken, tokenizers, transformers, pytorch-lightning, torchmetrics, torchaudio, av, Pydantic, and psutil. Both are written in Python.

# ray vs GPT-SoVITS

ray and GPT-SoVITS share 20 technologies: FastAPI, Hugging Face, starlette, Gradio, matplotlib, einops, onnxruntime, openai-whisper, peft, safetensors, sentencepiece, tiktoken, tokenizers, transformers, pytorch-lightning, torchmetrics, torchaudio, av, Pydantic, and psutil. Both are written in Python.

- [ray-project/ray](https://seerepo.com/r/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.
- [RVC-Boss/GPT-SoVITS](https://seerepo.com/r/RVC-Boss/GPT-SoVITS): 1 min voice data can also be used to train a good TTS model! (few shot voice cloning)

## What they share and what sets them apart

- In common: FastAPI, Hugging Face, starlette, Gradio, matplotlib, einops, onnxruntime, openai-whisper, peft, safetensors, sentencepiece, tiktoken, tokenizers, transformers, pytorch-lightning, torchmetrics, torchaudio, av, Pydantic, psutil
- Only in ray: amqp, async-lru, azure-common, azure-datalake-store, azure-storage-blob, confluent-kafka, diskcache, expiringdict, gitdb, google-cloud-core, h5py, kombu, pickleshare, pylance, pymongo, pyarrow, aioboto3, MongoDB, Redis, adlfs, smart-open, pyiceberg, pymysql, clickhouse-connect, deltalake, gcsfs, Celery, fastavro, pyzmq, s3fs, webdataset, Google, Google Cloud Storage, Kafka, asgiref, Flask, flask-cors, graphene, graphql-core, graphql-relay, jupyter-core, jupyterlab-server, werkzeug, Ray, AIOHTTP, Lightning, anyio, tornado, uvicorn, React, react-router-dom, alabaster, cycler, fonttools, jupyterlab-pygments, pydata-sphinx-theme, soupsieve, sphinx-design, tinycss2, contourpy, glfw, jupyter-server-terminals, jupyterlab-widgets, matplotlib-inline, Plotly, prompt-toolkit, pyopengl, Textual, widgetsnbextension, xyzservices, ipywidgets, Rich, pydot, alembic, peewee, sqlglot, SQLAlchemy, argon2-cffi, argon2-cffi-bindings, azure-identity, flask-basicauth, google-auth-oauthlib, itsdangerous, joserfc, jwcrypto, keyring, msal, msal-extensions, oauth2client, oauthlib, pyjwt, requests-oauthlib, cryptography, google-auth-httplib2, albucore, bitsandbytes, cmdstanpy, crcmod, cupy-cuda12x, cupy-cuda13x, fairscale, gradio-client, gym, LangChain, llvmlite, lm-eval, ml-dtypes, MLflow, nltk, ONNX, onnxscript, opt-einsum, orbax-checkpoint, prophet, rouge-score, sacrebleu, scikit-image, skops, tf-keras, timm, torchtext, triton, gymnasium, torch, TensorFlow, jax, torchvision, xgboost, lightgbm, scikit-learn, accelerate, datasets, evaluate, flax, Keras, albumentations, deepspeed, diffusers, hyperopt, Optuna, pettingzoo, tensordict, tensorflow-datasets, tensorflow-probability, bleach, defusedxml, et-xmlfile, imageio, imageio-ffmpeg, imagesize, jsonlines, linkify-it-py, lxml, mako, markdown, markdown-it-py, markupsafe, mdurl, mistune, moviepy, nbconvert, nh3, openpyxl, pandocfilters, ruamel-yaml, webencodings, xlrd, xmltodict, pillow, docutils, jinja2, beautifulsoup4, nbformat, torchcodec, annotated-types, fastjsonschema, fqdn, jsonschema-specifications, pathvalidate, pydantic-core, referencing, rfc3339-validator, rfc3986, rfc3986-validator, validators, jsonschema, openapi-schema-validator, aiobotocore, azure-mgmt-compute, azure-mgmt-resource, colorlog, Gunicorn, opentelemetry-api, opentelemetry-instrumentation, opentelemetry-semantic-conventions, python-json-logger, boto3, botocore, prometheus-client, OpenTelemetry, kubernetes, opentelemetry-exporter-prometheus, docker, opentelemetry-exporter-otlp-proto-grpc, opentelemetry-instrumentation-fastapi, typeface-roboto, MUI, usehooks-ts, lowlight, react-window, react-icons, @mui/icons-material, js-yaml
- Only in GPT-SoVITS: oss2, ctranslate2, faster-whisper, funasr, ModelScope, onnxruntime-gpu, python-mecab-ko, torch-complex, triton-windows, umap-learn, librosa, x-transformers, flash-attn, g2p-en, ffmpeg-python

## Side by side

| | ray | GPT-SoVITS |
|---|---|---|
| Size | 1,531,664 lines written, 2,777 code files | 50,422 lines written, 144 code files |
| Who writes it | 3.6% of its commits signed by AI. With Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex | 0.2% of its commits signed by AI. With Cursor |
| Activity | Last push November 6, 2026, 32,373 commits, 44,213 stars | Last push November 9, 2026, 895 commits, 64,647 stars |
| Tests | 2,168 test files. 9.7% of its code files have a test that imports them | 2 test files. 3.5% of its code files have a test that imports them |

- Size: Lines written by people and agents, without generated ones; code files, without tests.
- Who writes it: A commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
- Activity: From GitHub and its history, on the day SeeRepo read it.
- Tests: The files that test the code, and the share of code files a test imports.

## Frequently asked questions

### Which is bigger, ray or GPT-SoVITS?

ray, with 1,531,664 lines written; GPT-SoVITS has 50,422.

The proof: [ray-project/ray's code at commit 77567c5](https://github.com/ray-project/ray/tree/77567c5c5790e9e91aa40a5af93004ef958c2ffc)

### Which has more GitHub stars, ray or GPT-SoVITS?

GPT-SoVITS, with 64,647 stars; ray has 44,213.

The proof: [RVC-Boss/GPT-SoVITS on GitHub](https://github.com/RVC-Boss/GPT-SoVITS)

### Which has more tests, ray or GPT-SoVITS?

ray, with 2,168 test files; GPT-SoVITS has 2.

The proof: [ray-project/ray's code at commit 77567c5](https://github.com/ray-project/ray/tree/77567c5c5790e9e91aa40a5af93004ef958c2ffc)

### Which was updated more recently, ray or GPT-SoVITS?

GPT-SoVITS: its last push was on November 9, 2026, and ray's on November 6, 2026.

The proof: [RVC-Boss/GPT-SoVITS's commits on GitHub](https://github.com/RVC-Boss/GPT-SoVITS/commits)

### Which has more commits signed by AI, ray or GPT-SoVITS?

ray: an AI signed 3.6% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex; in GPT-SoVITS, 0.2%.

The proof: [the commits each tool signed in ray-project/ray](https://seerepo.com/r/ray-project/ray/ai)

## Sources

- ray-project/ray: Read on November 6, 2026, at commit 77567c5 (https://github.com/ray-project/ray/tree/77567c5c5790e9e91aa40a5af93004ef958c2ffc)
- RVC-Boss/GPT-SoVITS: Read on November 9, 2026, at commit 59c4468 (https://github.com/RVC-Boss/GPT-SoVITS/tree/59c44686f5cb9ffca9d8f1dec8b9c6836a129754)

## What is your repo built with?

Any public repo, with no account: https://seerepo.com/r/owner/repo/built, with the owner and name it has on GitHub.