Models

Designed for greater capability, faster inference, higher throughput, and scaling to larger models.

Z.ai's flagship model and the most capable open-weights model for coding, with major gains on long-horizon agentic tasks.

Z.ai's first natively multimodal model, approaching Claude Opus 4.8 on coding and agentic benchmarks with just 18B active parameters.

Turn text, structured data, and images into scored choices, yes/no answers, and ratings.

Phonon is Gradium’s text-to-speech family. It turns written text into spoken audio as it generates, making it useful for reading assistant replies, narrating passages, and adding a voice to local apps.

Bonsai 2 from Prism ML is a family of vision models built for ternary weights – smaller models with close to full-precision quality.

As a next-generation Flash model, M3.1 Flash delivers a generational leap in agentic tasks, coding, Computer Use and cybersecurity, while making online inference nearly three times faster and reducing usage costs by 70%.

Beam is an open model by Reflection designed to deliver strong performance for areas such as agentic tool use, coding and general reasoning with an emphasis on token efficient usage.

A 4B decision model from Together AI for fast classification.

EmbeddingGemma 2 is a multimodal embedding model from Google built on the Gemma 4 architecture.

Flint is a 39.8 billion-parameter mixture-of-experts model from Recursive, built for coding agents.

A 9B decision model from Bespoke Labs for fast, typed classification.

d1 is a 3B decision model from Liquid AI, built on LFM2.5-VL-3B

Clef is a 27B multimodal model created by Cloudflare that turns a state and a schema of typed questions into decisions.

Clef-Flash is a 9B multimodal model that turns a state and a schema of typed questions into decisions.

Nemotron 3.5 Bolt is NVIDIA’s compact vision-language model for local coding, reasoning, and tool use.

A 9B decision model from Bespoke Labs for fast classification, routing, and scoring.

Muse Spark Open is a natively multimodal model with 816B total parameters (42B active) and a 1M-token context window. Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning.

d1-omni is a multimodal 600M decision model from Liquid AI

pplx-decider is a 27B decision model from Perplexity, fine-tuned from Qwen3.8-27B