gpt-oss-20b delivers strong performance with fast inference and efficient reasoning, and is available on every plan, including Free.

A 27B-parameter multimodal model from Alibaba's Qwen team, built as an image-text-to-text model with a 256K-token context window and function calling.

Meta's Llama 3.3 — a 70B instruction-tuned model and one of the most widely benchmarked open models available, with function calling support.

A cutting-edge model designed for high-level reasoning, instruction-following, and advanced agent capabilities — strong across both general-purpose and specialized applications.

Alibaba's largest Qwen3.5 model — 397B parameters and a 256K context window, built for the most demanding reasoning and multimodal tasks.

Google DeepMind's Gemma 4 26B A4B — an instruction-tuned mixture-of-experts model with 25.2B total parameters but only 3.8B active per token, giving near-31B quality at MoE-efficient cost. Genuinely multimodal (text, images, and short video), with a 256K context window, native function calling, a toggleable reasoning mode, and structured output support. Scores 77.1% on LiveCodeBench v6 and 88.3% on AIME 2026. Apache 2.0. For vision requests, set max_tokens to at least 1000–1500 — the model spends part of its budget on internal reasoning before producing a visible answer.

Zhipu AI's GLM 5.2.

DeepSeek's fast, low-cost V4.1 variant.

DeepSeek's flagship V4 Pro.

Moonshot AI's Kimi K2.7, tuned for code.

Moonshot AI's flagship Kimi K3.

MiniMax's M3.