Trainy
AvailableBest for AI developers and enterprises needing to rapidly fine-tune large language models without managing DeepSpeed or Kubernetes clusters.
GPUs: H100, A100 (Managed Clusters)
$0.71/hr
ViewUse Case
Best GPU Cloud for LLM Fine-Tuning (2026)
Compare 1 GPU cloud providers optimised for LLM Fine-Tuning. Get infrastructure recommendations, pricing benchmarks, and instant quotes.
Get Matched with Providers →GPU Cloud for LLM Fine-Tuning
Find the best GPU cloud providers for LLM Fine-Tuning workloads. Compare infrastructure requirements, pricing, and provider availability on ComputeStacker.
Infrastructure Requirements for LLM Fine-Tuning
- Sufficient GPU VRAM for your model
- Reliable uptime SLA
- Competitive pricing
- Good support
Recommended GPUs for LLM Fine-Tuning
H100, A100, RTX 4090 (depends on workload)
Cost Breakdown
Pricing varies by provider and GPU type. Use the comparison tool to find the best rates for your specific LLM Fine-Tuning workload.
How to Get Started with LLM Fine-Tuning on GPU Cloud
- Define your requirements: GPU type, VRAM, number of GPUs, storage, location
- Compare providers: Use ComputeStacker to filter by GPU type, region, and price
- Request quotes: Submit your requirements and get proposals within 24 hours
- Start small, scale fast: Begin with single-GPU testing before committing to larger clusters
1 Providers for LLM Fine-Tuning
Frequently Asked Questions
The recommended GPU for LLM Fine-Tuning is: H100, A100, RTX 4090 (depends on workload). The best choice depends on your model size, budget, and latency requirements. ComputeStacker's comparison tool helps you match your workload to the right hardware.
Pricing varies by provider and GPU type. Use the comparison tool to find the best rates for your specific LLM Fine-Tuning workload.
ComputeStacker currently lists 1 providers with infrastructure suitable for LLM Fine-Tuning workloads. Use the filters to narrow by GPU type, location, and budget.
Yes — use ComputeStacker's quote request system. Describe your LLM Fine-Tuning requirements and receive proposals from multiple providers within 24 hours. No commitment required.