Ray Tune vs Together AI Fine-tuning

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Ray Tune Fine-tuning	Together AI Fine-tuning Fine-tuning
Tagline	Open-source Python library for distributed hyperparameter tuning at any scale.	Managed fine-tuning platform for open-source LLMs and vision models with LoRA, full fine-tuning, and RL support.
Category	Fine-tuning	Fine-tuning
Pricing	Free· Open-source (Apache 2.0); managed via Anyscale offers a $100 starting credit	Paid· Usage-based; cost estimator in-product, no public price list
Model	—	Multi-model (any Hugging Face open-source model)
Editorial score	8.1 / 10	8.1 / 10
Use cases	hyperparameter-tuningdistributed-trainingmodel-selectionpopulation-based-trainingearly-stopping	llm-fine-tuningvision-fine-tuningreinforcement-learningtool-calling-trainingdomain-adaptation
Pros	Scales the same code from a laptop to a multi-node GPU cluster Built-in PBT, ASHA, HyperBand plus Optuna/Ax/BOHB integrations Framework-agnostic: PyTorch, TF/Keras, XGBoost, Transformers Fault-tolerant with automatic checkpointing and trial resumption Free and open-source under Apache 2.0	Supports any open-source model on Hugging Face Hub LoRA, full fine-tune, RL, and tool-calling in one platform Vision fine-tuning on raw image data (Llama-4, Qwen3-VL) SOC 2 Type II + ISO 27001 with regional data residency Direct deploy to Together's inference stack after training
Cons	No GUI; everything is configured in Python Ray cluster setup adds operational overhead vs single-node tools Steeper learning curve than Optuna for simple sweeps	No public pricing — cost estimator only after signup Closed-source platform despite open-weight focus Overkill for hobbyists who just want a quick LoRA
Website	docs.ray.io	www.together.ai

Pick Ray Tune if

✅ Scales the same code from a laptop to a multi-node GPU cluster
✅ Built-in PBT, ASHA, HyperBand plus Optuna/Ax/BOHB integrations
✅ Framework-agnostic: PyTorch, TF/Keras, XGBoost, Transformers
✅ Fault-tolerant with automatic checkpointing and trial resumption

Pick Together AI Fine-tuning if

✅ Supports any open-source model on Hugging Face Hub
✅ LoRA, full fine-tune, RL, and tool-calling in one platform
✅ Vision fine-tuning on raw image data (Llama-4, Qwen3-VL)
✅ SOC 2 Type II + ISO 27001 with regional data residency

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