17,000+ LLMs Now Available on Backboard

We have expanded the Backboard model ecosystem to include over 17,000 large language models, giving independent developers access to one of the largest and most flexible AI model collections available through a single API.

A significant portion of these models come from our partners at Featherless, who specialize in curating and maintaining high-quality open source models for real-world workloads.

What this unlocks for builders

Real choice, not forced defaults
With access to 17,000+ models, you are no longer constrained to a short list of general-purpose LLMs. You can choose models based on cost, speed, size, or specialization, and switch them without reworking your application.

Purpose-built open source models
Many of the newly available models are optimized for narrow tasks such as coding, reasoning, classification, summarization, and domain-specific inference.

Tool-capable models at scale
Approximately 60 percent of the models support custom tools, including retrieval-augmented generation, search, and external function calls.

Clear model discoverability
All models that support tool calling are documented in the Backboard model library.

One API, consistent memory and state
Every model runs through the same Backboard API, with consistent handling of memory, state, routing, and tools.

Example: a lightweight research agent

Consider a simple research agent built by an independent developer:

• A small, fast open source model handles query understanding and routing

• A tool-capable model performs retrieval over documentation using RAG

• A separate summarization model produces concise, structured outputs

Because all three models are available behind one Backboard API, the developer can mix and match without managing multiple SDKs or infrastructure.

Partner spotlight: Featherless

Featherless provides a deep catalog of specialized open source models, many designed to work seamlessly with tools and external systems.

Get started

• Explore the model library to find tool-capable models

• Test specialized open source models for cost and performance gains

• Build and route across multiple models using a single Backboard integration