Thunder Compute
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Thunder Compute is a Y Combinator-backed startup that provides serverless GPU cloud computing services, allowing developers to run their existing code on cloud GPUs in under one minute without complex infrastructure management.
https://thundercompute.com?ref=aipure
Product Information
Updated:Feb 16, 2025
Thunder Compute Monthly Traffic Trends
Thunder Compute received 1.5k visits last month, demonstrating a Moderate Growth of 21.6%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history trafficWhat is Thunder Compute
Founded in 2024 by Brian Model and Carl Peterson, Thunder Compute is a cloud platform specifically optimized for prototyping with GPUs. The company was inspired when Brian noticed his research lab was using Excel sheets to schedule GPU time weeks in advance, leading to the realization that GPU cloud systems were constrained by physical connections between instances and GPUs. Based in Atlanta, GA, Thunder Compute aims to revolutionize GPU access by making it dramatically more efficient through virtualization, similar to how Amazon EBS virtualized storage and VMWare virtualized x86 processors.
Key Features of Thunder Compute
Thunder Compute is a serverless GPU cloud computing platform that allows developers to run their existing code on cloud GPUs in under 1 minute. It offers network-attached GPUs that behave like physically attached GPUs, with simple setup through a single command line interface. The platform provides flexible pricing where users only pay for active GPU usage, measured down to the second, and enables seamless scaling from prototyping to large-scale deployments without requiring separate configurations or environments.
Serverless GPU Infrastructure: Provides virtualized GPUs over TCP that can be accessed without managing physical infrastructure or complex driver configurations
Simple Integration: One-line command installation and setup through 'pip install tnr', allowing developers to keep their local codebase without additional configurations
Pay-Per-Second Pricing: Cost-effective billing model where users only pay for active GPU usage, measured in seconds, eliminating costs for idle resources
Instant Scalability: Ability to scale from single GPU prototyping to multi-GPU clusters with simple commands
Use Cases of Thunder Compute
AI/ML Model Development: Data scientists can prototype and develop AI/ML models without worrying about infrastructure setup and management
Research Labs: Academic and research institutions can efficiently share and allocate GPU resources among multiple users without advance scheduling
Enterprise AI Projects: Companies can run multiple AI instances for different projects while optimizing costs through usage-based billing
Pros
Simple setup and integration process
Cost-effective with pay-per-second billing
No need for separate configuration or environments
Up to 5x higher GPU utilization through virtualization
Cons
Performance may be lower when using remote GPU connections compared to physical GPUs
Limited to NVIDIA T4 shared instances during beta phase
How to Use Thunder Compute
Install Thunder Compute CLI: Run 'pip install tnr' command to install the Thunder Compute command line interface
Create an account: Sign up for a Thunder Compute account and generate an authentication token that will be used to log in to the CLI
Start a CPU instance: Use the command 'tnr start' to start a CPU-only instance for development. Optionally use --sync flag to synchronize your working directory with the instance
Access GPU resources: When you need GPU computing power, use Thunder Compute CLI commands to connect to virtual GPUs. The platform provides NVIDIA T4 shared instances during beta
Run Jupyter notebooks (optional): To access Jupyter notebooks within a Thunder Compute instance, use the 'notebook' command
Direct GPU connection (optional): Subscribers can directly connect a remote GPU to their local environment using specific tnr commands, though this may have lower performance than accessing through an instance
Disconnect when done: Disconnect from GPU resources when not in use - you only pay for active GPU time measured down to the second
Thunder Compute FAQs
Thunder Compute is a serverless GPU cloud computing platform that allows developers to run their existing code on cloud GPUs in under 1 minute, offering flexible and simple setup without requiring separate codebases or complex infrastructure management.
Official Posts
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Analytics of Thunder Compute Website
Thunder Compute Traffic & Rankings
1.5K
Monthly Visits
#7555247
Global Rank
-
Category Rank
Traffic Trends: Oct 2024-Jan 2025
Thunder Compute User Insights
00:00:26
Avg. Visit Duration
2.7
Pages Per Visit
34.19%
User Bounce Rate
Top Regions of Thunder Compute
US: 78.86%
IN: 21.14%
Others: 0%