Best AI tools for hosted fine tuning

Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).

Serverless GPUs and infra for training & serving ML.

One-API platform for running and fine-tuning open-source models.

Fine-tune GPT-4o-mini and friends on your own data.

Meta's open-weight LLM family covering 1B mobile models up to 405B frontier and natively multimodal 10M-context Llama 4 variants.

On-demand GPU cloud and serverless inference platform built specifically for AI workloads.

AI-native GPU cloud built for large-scale training, fine-tuning, and inference on NVIDIA hardware.

Declarative, YAML-driven deep learning framework for fine-tuning LLMs and multi-modal models without writing training loops.

Fine-tuning and reinforcement learning platform for turning expensive prompts into cheap, fast, task-specific models.

Open-source high-throughput inference engine for LLMs and multimodal models with OpenAI-compatible serving.

No-code fine-tuning and training pipeline that spins up state-of-the-art models on the Hugging Face Hub.

On-demand NVIDIA GPU cloud built specifically for training, fine-tuning, and serving large AI models.

Open-source Python framework for automated hyperparameter optimization across any ML stack.

Managed fine-tuning platform for open-source LLMs and vision models with LoRA, full fine-tuning, and RL support.

End-to-end platform for training and deploying ML models on microcontrollers, sensors, and other edge hardware.

Ray-powered platform for training, serving, and scaling LLMs.

Production inference and fine-tuning platform for open-source LLMs, tuned for speed and enterprise economics.

Memory-tuning platform for grounding LLMs in your facts.

Distributed training, fine-tuning, and serving platform with federated learning roots.

Kubernetes-native data versioning and pipeline engine for reproducible ML at petabyte scale.

Kubernetes-native MLOps platform for deploying and orchestrating ML and generative AI models in production.

Open-source, no-code WebUI for fine-tuning 100+ open LLMs with LoRA, QLoRA, DPO, and PPO.

End-to-end MLOps platform with GPU notebooks, training jobs, and model deployment, now folded into DigitalOcean.

Open-source automated machine learning that handles feature engineering, model selection, and stacked ensembling out of the box.

Enterprise agent platform from Scale AI that connects your data, orchestrates multi-agent workflows, and learns from human feedback inside your own VPC.

Hyperparameter optimization from Weights & Biases with Bayesian search and Hyperband early stopping.

Fine-tune and serve open-source LLMs on your own data without managing GPUs.

GitHub-style collaboration platform for ML datasets, experiments, and models with MLflow and DVC under the hood.

Serverless GPU orchestration that runs AI training and batch jobs without Docker or Kubernetes.