FriendliAI

What it does

FriendliAI is an inference platform for serving AI models through an API. You can deploy any of 630,000 Hugging Face models with one click, or bring your own fine-tuned or proprietary models. The platform handles deployment, scaling and performance tuning, and returns model responses with monitoring built in.

Teams typically use it in one of two ways: Model APIs, where you call a hosted model with a simple API request, or Dedicated Endpoints, where a model runs on dedicated GPUs you choose. The platform emphasizes low latency and throughput through optimizations such as custom GPU kernels, continuous batching and speculative decoding, along with a 99.99% uptime SLA on geo-distributed infrastructure.

FriendliAI suits developers and engineering teams building production AI applications where latency and cost per token matter. Dedicated Endpoints pricing is published per GPU-hour, billed per second. Model API rates and BYOG setups are confirmed on the pricing page or with sales, and enterprise terms such as VPC or on-prem deployment are arranged by contract.

What it can do

• Deploy any Hugging Face model with one click
• Bring your own fine-tuned or proprietary models
• Custom GPU kernels, continuous batching and speculative decoding for faster inference
• Autoscaling for fluctuating traffic
• Dedicated Endpoints billed per second on A100, H100, H200, B200 and B300 GPUs
• Built-in monitoring and compliance-ready architecture

Example workflows

Serve a Hugging Face model via API

Input: a model chosen from the 630,000 Hugging Face catalog. Steps: select the model, deploy with one click, call the API. Output: a hosted endpoint serving model responses with autoscaling and monitoring.

Run a custom model on dedicated GPUs

Input: a fine-tuned or proprietary model and a chosen GPU type. Steps: upload or reference the model, create a Dedicated Endpoint, scale as needed. Output: a dedicated endpoint billed per second of GPU use.

Before you choose

• Dedicated Endpoints bill per GPU-second for compute used, with no extra charge for start-up time.
• Enterprise features such as custom rate limits, VPC or on-prem deployment are enabled per contract rather than as a fixed bundle.
• Check the pricing page for current Model API rates before budgeting.

Listed under

• Coding
• Sandboxes and infrastructure
• API
• Developers
• Enterprise
• GPU cloud
• Inference
• Model hosting

Get started

Start from the team console, or talk to an engineer for enterprise needs.

1. Create an account and open the default team console at friendli.ai/suite/default-team/overview.
2. Issue an API key from the console to authenticate requests.
3. Choose Model APIs or Dedicated Endpoints, then deploy your model and call it through the API.

Dedicated Endpoints are billed per GPU-second. Model API rates are listed on the pricing page; BYOG pricing is tailored and requires contacting sales.

Source: friendli.ai/pricing, checked 29 Oct 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• FriendliAI | The Frontier AI Inference Cloud ↗friendli.ai
• FriendliAI Pricing for AI Inference: Model APIs, Dedicated GPUs, and BYOG ↗friendli.ai

Company website

friendli.ai: product, pricing and policy pages

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knowledge_base

Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.