deploybase

T4 on RunPod: Pricing, Specs & How to Rent

Deploybase · April 23, 2025 · GPU Pricing

Contents

Tesla T4 Hardware Specifications

The NVIDIA Tesla T4 delivers 16GB of GDDR6 memory coupled with 2,560 CUDA cores. Peak single-precision (FP32) performance reaches 8.1 TFLOPS, with 130 TOPS INT8 throughput for quantized inference. The T4 consumes just 70 watts, making it exceptionally efficient for small-to-medium inference workloads. Its low power profile enables cost-effective scaling.

Memory bandwidth of 320 gigabytes per second supports real-time inference at scale. The T4 excels at natural language processing inference, computer vision model serving, and small-scale model training. Support for INT8 precision reduces model sizes by 4x while maintaining accuracy for many applications.

The Tesla T4 has become the de facto GPU for cost-conscious teams. Since introduction in 2018, millions of T4s have been deployed across cloud providers. Established software ecosystem and mature driver support make T4 instances stable and reliable.

T4 on RunPod: Pricing and Availability

RunPod offers Tesla T4 GPU access at competitive rates. As of March 2026, T4 instances cost approximately $0.20-$0.25 per hour depending on region. This makes T4 one of the most affordable GPU options in the RunPod catalog. Spot pricing drops rates further, often reaching $0.10-$0.15 per hour.

Availability remains excellent across RunPod's global data center network. T4s are among the most available GPUs due to lower demand compared to newer generations. Pod provisioning typically completes within seconds. Multiple pods can launch simultaneously without capacity constraints.

RunPod includes 50GB of temporary storage with T4 rentals. Additional persistent storage costs $0.10 per GB-month. Bandwidth charges apply at $0.01 per GB outside the data center. Direct data transfers between pods remain free.

Cost Analysis vs Other Providers

Lambda Labs does not offer T4 pricing through their API. AWS charges approximately $0.526 per hour for T4 instances (g4dn.xlarge on-demand), substantially more than RunPod. Google Cloud offers T4 access through Colab, which provides free tier options plus paid premium access.

RunPod's T4 pricing represents 50-60% savings compared to AWS on-demand rates. Even with bandwidth charges, projects running T4 workloads on RunPod cost less than equivalent AWS deployments. Teams evaluating multiple cloud options should consider RunPod for T4-scale workloads.

Spot instance pricing makes RunPod highly competitive. At $0.10-$0.15 per hour, T4 instances provide significant savings over on-demand. Workloads tolerating occasional interruptions benefit from meaningful cost reductions.

Ideal Use Cases

T4 GPUs suit inference-heavy applications where training is minimal. Language model serving, image classification, object detection, and text generation systems run efficiently on T4. Batch processing pipelines complete within reasonable timeframes despite modest compute.

Small-scale fine-tuning of pre-trained models works well on T4. Single-GPU fine-tuning often completes within hours. Teams prototyping before scaling to larger GPUs use T4 for proof-of-concept work.

Computer vision preprocessing benefits from T4 capabilities. Model compression techniques like quantization and distillation benefit from T4's efficient execution of lighter workloads.

Production services with modest traffic patterns fit T4 perfectly. APIs serving hundreds of requests per second scale across multiple T4 pods cost-effectively. Burst traffic handling uses spot instances to absorb peak demand without contract commitments.

Getting Started

Start at RunPod.io and filter for Tesla T4. Compare regional pricing and pick the cheapest option. Pre-configured templates exist for PyTorch, TensorFlow, and NVIDIA CUDA.

Hit "Rent" and RunPod provisions the instance in seconds. SSH details come back immediately. Run nvidia-smi to confirm the GPU is there.

Clone model repos from GitHub or download from Hugging Face. Install framework dependencies, test inference on sample data, set up API keys.

For production, use RunPod's network volumes for persistent model storage. Auto-scaling pod groups handle load balancing automatically. Track usage and adjust allocation as needed.

FAQ

Q: What does Tesla T4 cost on RunPod? A: Tesla T4 costs approximately $0.20-$0.25 per hour on-demand, with spot instances dropping to $0.10-$0.15 per hour depending on region.

Q: Is T4 suitable for model training? A: T4 works for small-scale training and fine-tuning. Full model training on large datasets takes longer than on A100 or H100 systems. Inference workloads are the primary strength.

Q: How long does a T4 pod take to launch on RunPod? A: Most T4 pods launch within seconds due to high availability. Provisioning rarely takes longer than 30 seconds.

Q: Can I save money with long-term T4 rentals? A: RunPod offers 10-20% discounts for monthly commitments. Annual commitments provide steeper discounts for continuous workloads.

Q: What programming frameworks run on T4? A: PyTorch, TensorFlow, ONNX Runtime, and vLLM all run efficiently on T4. Choose frameworks matching existing codebases.

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