Serverless model access
Featherless exposes open-weight models through serverless APIs, so users can call models without provisioning or managing their own inference servers.
Featherless
Freemium
Serverless AI inference API for open-weight models
What is Featherless?
Featherless is a serverless AI inference platform focused on hosting open-weight language models through an API. Its homepage and docs describe a single API key that gives access to a large and continually expanding model library, including popular families such as Qwen, Llama, Mistral, DeepSeek, and RWKV.
The product is aimed at developers who want to call open models without managing their own infrastructure. The documentation covers getting started, API reference material, models and compatibility, concurrency limits, tool calling, vision, embeddings, and application guides, which suggests a platform built for both experimentation and production use.
What can Featherless do?
Large open-model library
The platform presents a large, searchable model library with more than 30,000 models on the homepage and a broader catalog view on the models page.
API endpoints for common LLM tasks
The docs point to common endpoints for listing models, chat, text completions, tokenization, and streaming, which supports a standard API workflow.
Developer documentation
Documentation sections cover quickstart, models and compatibility, plans, concurrency limits, tool calling, vision, embeddings, and application guides.
Catalog filtering and discovery
The models page includes filters for architecture, language, domain, training, license, modality, capability, release recency, and popularity, which helps narrow the catalog.
Tiered plan constraints
The pricing page shows plan-based limits such as model-size access, concurrent connections, and context window caps.
Use Cases
“Ship an app with hosted model inference”
Use Featherless when you want to call open models from an application without running your own inference stack. The platform is positioned around serverless API access and a single API key.
“Evaluate and select a model from the catalog”
Use the model browser to compare families, capabilities, and release recency before choosing a model for a task such as coding, reasoning, chat, or roleplay.
“Prototype against common LLM endpoints”
Use the documentation as a starting point for implementing chat, completions, streaming, tokenization, tool calling, vision, or embeddings in a product workflow.
“Match usage to an available plan”
Use the plan pages to understand whether your workload fits the visible concurrency and context limits before you adopt the service more broadly.
“Work with specific open-model families”
Use the site’s model pages and docs to explore open-weight model compatibility if you need to support a specific family such as Qwen, Llama, Mistral, DeepSeek, or RWKV.
Frequently Asked Questions
What is Featherless used for?
Featherless is a serverless AI inference platform that exposes open-weight models through API endpoints. The overview and docs point to API access for model inference, with quickstart material for making a first API call.
How do developers interact with the platform?
The docs say Featherless provides a continually expanding library of open-weight models and references common API endpoints such as `/v1/models`, `/v1/chat/completions`, `/v1/completions`, and `/v1/tokenize`.
Does Featherless have paid plans?
The pricing page shows paid plans rather than a free-only product: Basic is listed at $10 per month and Premium at $25 per month. The source does not provide a full pricing matrix beyond those plan summaries.
Are there usage limits?
The documentation includes a concurrency-limits section and the pricing page lists connection caps on the visible plans, so usage is plan-dependent. The source does not provide enough detail to describe broader account-sharing or team-workspace behavior.
Who is Featherless for?
The site positions Featherless for open-model hosting and API use, while also pointing users to Phoenix for chatting with models on the Featherless site. That suggests the platform serves both API builders and people who want to try models directly.
Quick Facts
- Category
- Serverless LLM hosting
- Platform
- Web and API
- Primary users
- Developers building with open-weight models
- Domain
- featherless.ai
- Notable workflows
- Model browsing, API inference, chat completions, completions, tokenization, tool calling
- Pricing signal
- Paid plans are listed, including Basic and Premium
Featherless Traffic Analysis
Traffic data is for reference only.
- Domain Rating
- 64
Featherless Alternatives
Zro
zro.moonmath.ai
Zro is a private inference endpoint for coding agents, serving open-weight models on EU infrastructure. It supports OpenAI-compatible and Anthropic-compatible requests, plus launcher-based setup for several coding tools.
Hugging Face Inference Providers
huggingface.co
Hugging Face Inference Providers gives developers a way to compare supported models across infrastructure providers using model availability, pricing, context limits, latency, throughput, and capability indicators.
New API
www.newapi.ai
New API is an open-source, self-hosted AI gateway for developers and teams. It provides a unified OpenAI-compatible endpoint for connecting multiple AI providers, selecting models, configuring channels, and monitoring usage on their own infrastructure.