Fine-tuning large language models is no small feat—it demands high-performance GPUs, vast computational resources, and often, a wallet-draining budget. But what if you could get the same powerful infrastructure for a fraction of the cost? That’s where affordable cloud platforms come in.
Instead of paying premium rates on AWS, Google Cloud, or Azure, smart AI researchers and developers are turning to cost-effective GPU rental services that offer the same power at 5-6x lower prices. In this article, we’ll explore five of the cheapest cloud platforms for fine-tuning LLMs: Vast.ai, Together AI, Cudo Compute, RunPod, and Lambda Labs.
From real-time bidding systems to free-tier compute options, these platforms make cutting-edge AI research accessible, scalable, and budget-friendly. Let’s dive in and find the best cloud platforms for fine-tuning LLMs.
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Vast.ai
Vast.ai is a high-performance AI cloud platform that provides instant GPU rentals at significantly lower prices than traditional cloud providers. With 5-6x cost savings, real-time bidding, and secure, certified data center GPUs, Vast.ai is an excellent choice for AI researchers, developers, and enterprises fine-tuning large language models (LLMs).
Key Features
- Instant GPU Rentals: Get on-demand access to powerful GPUs with 24/7 live support.
- Cost Savings: Save 5-6x on cloud compute costs compared to mainstream providers.
- On-Demand or Interruptible Instances: Choose stable, predictable pricing or save an additional 50% with auction-based interruptible instances.
- Secure AI Workloads: Vast.ai offers certified data center GPUs and prioritizes data security to meet regulatory compliance needs.
- Real-Time Bidding System: Competitive auction pricing lets users bid on interruptible instances, further reducing costs.
- GUI and CLI Support: Easily search the entire GPU marketplace using a command-line interface (CLI) or GUI.
Best Use Cases
- AI startups looking for cost-effective cloud GPUs.
- Developers fine-tuning LLMs with scriptable CLI automation.
- Enterprises requiring secure, compliant GPU rentals for AI workloads.
- Researchers leveraging real-time bidding to save on compute costs.
Pricing
| GPU Type | Vast.ai | AWS | CoreWeave | Lambda Labs |
|---|---|---|---|---|
| RTX 5090 | $0.69/hr | — | — | — |
| H200 | $2.40/hr | $10.60/hr | $6.31/hr | — |
| H100 | $1.65/hr | $12.30/hr | $6.16/hr | $3.29/hr |
| RTX 4090 | $0.35/hr | — | — | — |
| RTX 3090 | $0.31/hr | — | — | — |
Together AI
Together AI is an end-to-end AI acceleration cloud designed for fast model training, fine-tuning, and inference on NVIDIA GPUs. It supports over 200 generative AI models, offering an OpenAI-compatible API that enables seamless migration from closed-source models.
With enterprise-grade security (SOC 2 & HIPAA compliance) and serverless or dedicated endpoints, Together AI is a powerful choice for AI developers looking for scalable, cost-effective GPU solutions for fine-tuning large language models (LLMs).
Key Features
- Full Generative AI Lifecycle: Train, fine-tune, or build models from scratch using open-source and multimodal models.
- Fine-Tuning Options: Support for full fine-tuning, LoRA fine-tuning, and easy customization via APIs.
- Inference at Scale: Serverless or dedicated endpoints for high-speed model deployment.
- Secure & Compliant: SOC 2 and HIPAA compliant infrastructure for enterprise AI workloads.
- Powerful GPU Clusters: Access to GB200, H200, and H100 GPUs for massive AI training workloads.
Best Use Cases
- Startups and enterprises looking to migrate from closed AI models to open-source alternatives.
- Developers fine-tuning LLMs with full customization and API support.
- Businesses requiring secure AI deployments with SOC 2 and HIPAA compliance.
- Teams running large-scale AI workloads on high-performance H100 and H200 GPUs.
Pricing
| Hardware Type | Price/Minute | Price/Hour |
|---|---|---|
| 1x RTX-6000 48GB | $0.025 | $1.49 |
| 1x L40 48GB | $0.025 | $1.49 |
| 1x L40S 48GB | $0.035 | $2.10 |
| 1x A100 PCIe 80GB | $0.040 | $2.40 |
| 1x A100 SXM 40GB | $0.040 | $2.40 |
| 1x A100 SXM 80GB | $0.043 | $2.56 |
| 1x H100 80GB | $0.056 | $3.36 |
| 1x H200 141GB | $0.083 | $4.99 |
Cudo Compute
Cudo Compute offers a high-performance GPU cloud designed for AI, machine learning, and rendering workloads. With on-demand GPU rentals, global infrastructure, and cost-saving commitment plans, Cudo Compute provides a scalable and budget-friendly solution for fine-tuning large language models (LLMs) and running AI workloads efficiently.
Key Features
- Wide Range of GPUs: Access NVIDIA and AMD GPUs optimized for AI, ML, and HPC workloads.
- Flexible Deployment: Deploy instances quickly using a dashboard, CLI tool, or API.
- Real-Time Monitoring: Track GPU usage, performance bottlenecks, and resource allocation for optimization.
- Global Infrastructure: Run AI model training and inference anywhere in the world with geo-distributed GPUs.
- Cost Management: Transparent pricing, detailed billing reports, and tools for cost optimization.
- Commitment Pricing – Save up to 30% on GPU costs by choosing long-term fixed-term plans.
Best Use Cases
- AI and ML model training that requires high-performance GPUs with global availability.
- Developers needing API and CLI-based GPU management for automation.
- Businesses looking to optimize costs with commitment pricing and real-time monitoring.
- Researchers requiring scalable GPU clusters for LLM fine-tuning and inference.
Pricing
| GPU Model | Memory & Bandwidth | On-Demand Price (/hr) | Commitment Price (/hr) | Potential Savings |
|---|---|---|---|---|
| H200 SXM | 141GB HBM3e (4.8 TB/s) | $3.99 | $3.39 | $1,307.12 |
| H100 SXM | 80GB HBM2e (3.35 TB/s) | $2.45 | $1.80 | $26,040.96 |
| H100 PCIe | 94GB HBM2e (3.9 TB/s) | $2.45 | $2.15 | $13,147.20 |
| A100 PCIe | 80GB HBM2e (1.9 TB/s) | $1.50 | $1.25 | $10,956.00 |
| L40S | 48GB GDDR6 (864 GB/s) | $0.88 | $0.75 | $3,419.52 |
| A800 PCIe | 80GB HBM2e (1.94 TB/s) | $0.80 | $0.76 | $87.36 |
| RTX A6000 | 48GB GDDR6 (768 GB/s) | $0.45 | $0.40 | $109.20 |
| A40 | 48GB GDDR6 (696 GB/s) | $0.39 | $0.35 | $87.36 |
| V100 | 16GB HBM2 (900 GB/s) | $0.39 | $0.23 | $4,103.42 |
| RTX 4000 SFF Ada | 20GB GDDR6 (280 GB/s) | $0.37 | $0.20 | $4,476.94 |
| RTX A5000 | 24GB GDDR6 (768 GB/s) | $0.35 | $0.30 | $109.20 |
RunPod
RunPod is a high-performance GPU cloud platform designed to seamlessly deploy AI workloads with minimal setup time. It eliminates infrastructure headaches, allowing developers and researchers to focus entirely on fine-tuning models rather than waiting for GPU availability. With ultra-fast cold-boot times and 50+ ready-to-use templates, RunPod makes deploying machine learning (ML) workloads easier and more efficient.
Key Features
- Ultra-Fast Deployment: Spin up GPU pods in milliseconds, reducing cold-boot wait times.
- Preconfigured Environments: Get started instantly with PyTorch, TensorFlow, or custom environments.
- Community & Custom Templates: Use 50+ prebuilt templates or create your own custom container.
- Globally Distributed Infrastructure: Deploy ML workloads in multiple data centers worldwide.
- Seamless Scaling: Expand GPU capacity as needed, optimizing for cost and performance.
Why Choose RunPod for Fine-Tuning LLMs?
- Instant model training: No long wait times; start fine-tuning immediately.
- Pre-built AI environments: Supports frameworks like PyTorch and TensorFlow out of the box.
- Customizable deployments: Bring your own container or choose from community templates.
- Global GPU availability: Ensures high availability and low-latency inference.
Pricing
| GPU Model | VRAM | RAM | vCPUs | Community Cloud Price | Secure Cloud Price |
|---|---|---|---|---|---|
| H100 NVL | 94GB | 94GB | 16 | $2.59/hr | $2.79/hr |
| H200 SXM | 141GB | N/A | N/A | $3.59/hr | $3.99/hr |
| H100 PCIe | 80GB | 188GB | 16 | $1.99/hr | $2.39/hr |
| H100 SXM | 80GB | 125GB | 20 | $2.69/hr | $2.99/hr |
| A100 PCIe | 80GB | 117GB | 8 | $1.19/hr | $1.64/hr |
| A100 SXM | 80GB | 125GB | 16 | $1.89/hr | $1.89/hr |
Lambda Labs
Lambda Labs offers high-performance cloud computing solutions tailored for AI developers. With on-demand NVIDIA GPU instances, scalable clusters, and priKvate cloud options, Lambda Labs provides cost-effective and efficient infrastructure for AI training and inference.
Key Features
- 1-Click Clusters: Instantly deploy NVIDIA B200 GPU clusters with Quantum-2 InfiniBand.
- On-Demand Instances: Hourly billed GPU instances, including H100 starting at $2.49/hr.
- Private Cloud: Reserve thousands of H100, H200, GH200, B200, GB200 GPUs with Quantum-2 InfiniBand.
- Lowest-Cost AI Inference: Serverless API access to the latest LLMs with no rate limits.
- Lambda Stack: One-line install & updates for PyTorch®, TensorFlow®, CUDA®, CuDNN®, NVIDIA Drivers.
Why Lambda Labs?
- Flexible Pricing: Hourly billing with on-demand access.
- High-Performance AI Compute: Quantum-2 InfiniBand for ultra-low latency.
- Scalable GPU Infrastructure: Single instances to large clusters.
- Optimized for AI Workflows: Pre-installed ML frameworks for quick deployment.
Pricing
| GPU Count | On-Demand Pricing | Reserved (1-11 months) | Reserved (12-36 months) |
|---|---|---|---|
| 16 – 512 NVIDIA Blackwell GPUs | $5.99/GPU/hour | Contact Us | Contact Us |
Conclusion
Fine-tuning large language models no longer has to be an expensive, resource-intensive endeavor. With cloud platforms like Vast.ai, Together AI, Cudo Compute, RunPod, and Lambda Labs offering high-performance GPUs at a fraction of the cost of traditional providers, AI researchers and developers now have access to scalable, affordable solutions. Whether you need on-demand access, long-term reservations, or cost-saving commitment plans, these platforms make cutting-edge AI training and inference more accessible than ever. By choosing the right provider based on your specific needs, you can optimize both performance and budget—allowing you to focus on innovation rather than infrastructure costs.
My name is Ayushi Trivedi. I am a B. Tech graduate. I have 3 years of experience working as an educator and content editor. I have worked with various python libraries, like numpy, pandas, seaborn, matplotlib, scikit, imblearn, linear regression and many more. I am also an author. My first book named #turning25 has been published and is available on amazon and flipkart. Here, I am technical content editor at Analytics Vidhya. I feel proud and happy to be AVian. I have a great team to work with. I love building the bridge between the technology and the learner.
