Boost AI Performance with Efficient On-Demand Fine-tuning
Train and optimize pre-trained models on your own datasets for better task-specific results at lower cost. NexGPU provides powerful GPU computing to make fine-tuning simple and efficient.
Purpose-Built for Fine-tuning
Custom Dataset Training
Train and optimize pre-trained models on your own datasets for better task-specific results. Supports LoRA, QLoRA, Full Fine-tuning and more.
Blazing Fast Training
Use powerful GPUs to reduce training time and cost. From RTX 4090 to H100, choose the right compute for your model size.
Flexible Resource Configuration
Customize storage, memory, and compute resources to match your model scale. From single-GPU to multi-GPU distributed training, scale on demand.
Seamless Deployment
After training, seamlessly deploy your fine-tuned model for inference. One-click model weight export for rapid service deployment.
Get Started: AI Fine-tuning Templates
Use pre-built fine-tuning templates to quickly start your model training tasks.
Axolotl
Streamline fine-tuning for various AI models with flexible configuration and architecture support. Supports LoRA, QLoRA, Full Fine-tuning, compatible with LLaMA, Mistral, Qwen and more.
Unsloth
High-performance fine-tuning framework, 2-5x faster than traditional methods with 60% less VRAM. Perfect for efficient fine-tuning on consumer GPUs.
LLaMA Factory
All-in-one LLM fine-tuning platform with Web UI, supporting 100+ models with SFT, RLHF, DPO and more training methods.
Why Fine-tune on NexGPU?
Save 80% on Costs
Dramatically lower GPU costs compared to AWS SageMaker and Azure ML. RTX 4090 from $0.28/hr, H100 from $1.65/hr.
Zero-Config Startup
Pre-built images for Axolotl, Unsloth, LLaMA Factory and other popular fine-tuning frameworks. Ready to use out of the box.
Multiple GPU Options
From RTX 3090 (24GB) to H100 (80GB), covering fine-tuning needs from 7B to 70B+ parameter models.
Data Security
End-to-end encrypted data transfer with private network isolation. One-click data cleanup after training for enterprise compliance.
Distributed Training
Support for DeepSpeed, FSDP and other distributed training frameworks. Multi-GPU parallel acceleration for large model fine-tuning.
Real-time Monitoring
Integrated WandB, TensorBoard and other training monitoring tools. Track loss, learning rate and other key metrics in real-time.
Recommended GPU Configurations
7B Parameter Models
Suitable for LoRA/QLoRA fine-tuning of LLaMA-2-7B, Mistral-7B, Qwen-7B and similar models.
13B-34B Parameter Models
Suitable for fine-tuning medium to large models like LLaMA-2-13B, CodeLlama-34B.
70B+ Parameter Models
Suitable for distributed fine-tuning of ultra-large models like LLaMA-2-70B, Qwen-72B.
Start Fine-tuning Your AI Models
Whether it's lightweight 7B fine-tuning or full-parameter 70B training, NexGPU provides the most cost-effective computing support.