Ray

Ray

Anyscale
Tinker

Tinker

Thinking Machines Lab
+
+

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About

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.

About

Tinker is a training API designed for researchers and developers that allows full control over model fine-tuning while abstracting away the infrastructure complexity. It supports primitives and enables users to build custom training loops, supervision logic, and reinforcement learning flows. It currently supports LoRA fine-tuning on open-weight models across both LLama and Qwen families, ranging from small models to large mixture-of-experts architectures. Users write Python code to handle data, loss functions, and algorithmic logic; Tinker handles scheduling, resource allocation, distributed training, and failure recovery behind the scenes. The service lets users download model weights at different checkpoints and doesn’t force them to manage the compute environment. Tinker is delivered as a managed offering; training jobs run on Thinking Machines’ internal GPU infrastructure, freeing users from cluster orchestration.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

ML and AI Engineers, Software Developers

Audience

AI researchers and ML engineers requiring a solution to experiment with fine-tuning open source language models while outsourcing infrastructure complexity

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Anyscale
Founded: 2019
United States
ray.io

Company Information

Thinking Machines Lab
United States
thinkingmachines.ai/tinker/

Alternatives

Alternatives

LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

Python
Amazon EC2 Trn2 Instances
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Dask
Databricks Data Intelligence Platform
Feast
Flyte
Google Cloud Platform
Kubernetes
LanceDB
Llama 3
Llama 3.1
Llama 3.3
MLflow
Qwen3
Snowflake
TensorFlow
io.net

Integrations

Python
Amazon EC2 Trn2 Instances
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Dask
Databricks Data Intelligence Platform
Feast
Flyte
Google Cloud Platform
Kubernetes
LanceDB
Llama 3
Llama 3.1
Llama 3.3
MLflow
Qwen3
Snowflake
TensorFlow
io.net
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