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Deploy and scale machine learning models on serverless GPUs in minutes.

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Reviews onCapterra
2 reviews tracked

The Bottom Line

Entry price

Free plan available, paid tiers above

Biggest pro

Eliminates infrastructure management for GPU clusters

Biggest con

Specific pricing details for enterprise plans require direct contact

TL;DR - Inferless

  • Deploys machine learning models to serverless GPUs rapidly.
  • Automatically scales GPU resources from zero to hundreds based on demand.
  • Offers usage-based billing and fast cold starts for cost-effective inference.
Pricing: Free plan available
Best for: Growing teams

What is Inferless?

Editorial review
Inferless provides a serverless GPU inference platform designed for deploying machine learning models quickly and affordably. It allows users to take a model file and deploy it as an endpoint in minutes, supporting deployments from Hugging Face, Git, Docker, or CLI with automatic redeploy options. The platform is engineered to handle spiky and unpredictable workloads, automatically scaling from zero to hundreds of GPUs using an in-house load balancer, ensuring efficient resource utilization and minimal overhead. This platform is ideal for machine learning engineers, data scientists, and developers who need to deploy compute-intensive deep learning models without managing underlying infrastructure. It offers features like custom runtimes, NFS-like writable volumes, automated CI/CD, and detailed monitoring. Inferless aims to optimize high-end computing resources, enabling companies to run custom models built on open-source frameworks efficiently and cost-effectively, with a focus on reducing cold starts and providing usage-based billing. Key benefits include zero infrastructure management, on-demand scaling with payment only for actual usage, and lightning-fast cold starts. The platform supports various GPU types like Nvidia A100, A10, and T4, and is built with enterprise-level security, including SOC-2 Type II certification and regular vulnerability scans. It's particularly beneficial for applications in computer vision, NLP, recommendations, and scientific computing.

Available on: Web

Pros & Cons

Pros

  • Eliminates infrastructure management for GPU clusters
  • Scales automatically with workload, paying only for usage
  • Achieves sub-second cold starts for large models
  • Provides significant cost savings compared to traditional GPU clusters
  • Offers enterprise-grade security with SOC-2 Type II certification

Cons

  • Specific pricing details for enterprise plans require direct contact
  • Currently in private beta for certain offerings, requiring waitlist access

Ratings Across the Web

4(2 reviews)

Ratings aggregated from independent review platforms. Learn more

Key Features

One-click deployment from Hugging Face, Git, Docker, or CLIAutomatic scaling from zero to hundreds of GPUsCustomizable container runtimesNFS-like writable volumes with simultaneous connectionsAutomated CI/CD for model re-importsDetailed call and build logs for monitoringDynamic batching for increased throughputCustomizable private endpoints (scale down, timeout, concurrency, testing, webhooks)

Pricing Plans

Free Trial

Pricing checked Jul 5, 2026

Starter

$0.000555 / sec

  • Designed for small teams and independent developers
  • Deploy models in minutes without worrying about the cost

Enterprise

Contact us

  • Built for fast-growing startups and larger organizations
  • Scale quickly at an affordable cost with desired latency results

Nvidia T4 Dedicated

$0.000185 / sec

  • GPU RAM: 16GB
  • vCPUs: 3x
  • RAM: 20GB

Nvidia A10 Dedicated

$0.000341 / sec

  • GPU RAM: 24GB
  • vCPUs: 7x
  • RAM: 30GB

Nvidia A100 Dedicated

$0.001491 / sec

  • GPU RAM: 80GB
  • vCPUs: 20x
  • RAM: 200GB

Nvidia T4 Shared

$0.000092 / sec

  • GPU RAM: 8GB
  • vCPUs: 1.5x
  • RAM: 10GB

Nvidia A10 Shared

$0.000170 / sec

  • GPU RAM: 12GB
  • vCPUs: 3x
  • RAM: 15GB

Nvidia A100 Shared

$0.000745 / sec

  • GPU RAM: 40GB
  • vCPUs: 10x
  • RAM: 100GB

Volume Pricing - Storage

Free 50GB/month, then $0.3/GB/month

  • 50 GB free every month
  • Extra storage costs $0.3/GB/month

Join Waitlist (Startup)

Contact us

  • Min 10,000 Inference Requests per month
  • Unlimited deployed webhook endpoints
  • GPU concurrency of 5
  • 15 day of log retention
  • Support via private Slack connect within 48 working hours
  • Include Credits : $30

Get Early Access (Enterprise)

Contact us

  • Min 100,000 Inference Requests per month
  • Unlimited deployed webhook endpoints
  • GPU concurrency of 50
  • 365 day of log retention
  • Support via private Slack connect & support engineer
  • Include Credits : Custom

Reviews

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Inferless FAQ

How does Inferless facilitate the deployment of machine learning models?

Inferless allows users to deploy machine learning models as endpoints in minutes by taking a model file and supporting deployments from sources like Hugging Face, Git, Docker, or CLI. It also offers automatic redeploy options to streamline the process.

Which teams would benefit most from using Inferless?

Inferless is ideal for machine learning engineers, data scientists, and developers who need to deploy compute-intensive deep learning models without the overhead of managing underlying infrastructure. It supports applications in areas such as computer vision, natural language processing, recommendations, and scientific computing.

How does Inferless compare to Baseten for model deployment?

Inferless focuses on deploying and scaling machine learning models on serverless GPUs with automatic scaling from zero to hundreds of GPUs and sub-second cold starts. It emphasizes zero infrastructure management and usage-based billing for efficient resource utilization, similar to how Baseten provides model deployment capabilities.

What kind of limitations should users be aware of when considering Inferless?

Specific pricing details for enterprise plans are not publicly listed and require direct contact. Additionally, some offerings are currently in private beta, meaning access may require joining a waitlist.

Does Inferless include a free tier, and how is its pricing structured?

Yes, Inferless offers a free tier for users to get started. For more extensive usage and additional features, paid plans are available, with billing based on actual usage rather than fixed infrastructure costs.

How does Inferless manage fluctuating workloads for deployed models?

Inferless is engineered to handle spiky and unpredictable workloads by automatically scaling from zero to hundreds of GPUs. It uses an in-house load balancer to ensure efficient resource utilization and minimal overhead, only charging for actual usage.

Can Inferless integrate with existing CI/CD pipelines?

Yes, Inferless supports automated CI/CD, allowing for seamless integration into existing development workflows. This feature helps automate the deployment process and maintain continuous delivery of machine learning models.