Best AI tools for gpu infrastructure

Together AI

Featured

Fine-tuning · Llama / Mistral / Qwen / DeepSeek and others

8.6

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

Modal

Fine-tuning · Infrastructure (any model you can host)

8.7

Serverless GPUs and infra for training & serving ML.

RunPod

Fine-tuning · Bring-your-own (any open-weight or custom model)

8.3

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

vLLM

Fine-tuning · Multi-model (open-weight LLMs: Llama, Qwen, DeepSeek, Mistral, Gemma, Phi, etc.)

8.3

Open-source high-throughput inference engine for serving LLMs with PagedAttention and continuous batching.

CoreWeave

Fine-tuning · DeepSeek

8.2

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

OpenPipe

Fine-tuning · Llama, Mistral, Qwen and other open-weight base models

8.2

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

Lambda

Fine-tuning · NVIDIA VR200 NVL72, NVIDIA GB300 NVL72, NVIDIA HGX B200, NVIDIA HGX B300, NVIDIA H100

8.1

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

FedML

Fine-tuning · Bring-your-own (PyTorch, Hugging Face)

7.3

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

Paperspace Gradient

Fine-tuning · Bring-your-own (PyTorch, TensorFlow, Hugging Face)

7.2

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

Colossal-AI

Fine-tuning · Framework-agnostic; used with LLaMA, GPT, Stable Diffusion, ViT, and other PyTorch-based open-weight models

Making large AI models cheaper, faster, and more accessible through distributed training

PyTorch Lightning

Fine-tuning · Framework-agnostic — trains any PyTorch model (transformers, CNNs, diffusion, RL nets, etc.)

The deep learning framework for professional AI researchers and ML engineers