Google: Gemini Omni 1.1 Flash Preview

Google: Gemma 4 26B A4B IT

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at a fraction of the compute cost. Supports multimodal input including text, images, and video (up to 60s at 1fps). Features a 256K token context window, native function calling, configurable thinking/reasoning mode, and structured output support. Released under Apache 2.0.

Google: Gemini 4 Argon

Gemini 4 Argon is a frontier model from Google DeepMind, released on September 30, 2026. It is the first model in the Gemini 4 series and uses a new naming scheme. It is strong in coding, financial research, legal drafting, and autonomously patching cybersecurity vulnerabilities. It accepts text, image, video, and file inputs and has a 1-million-token context window. On benchmarks, it scores 77.9% on DeepSWE v1.1, ahead of Claude Opus 5.5 and GPT-6 Astra, and ranks first on the Vals Index with 68.90%.

Google: Nano Banana 2.1 (Gemini Nano Banana 2.1)

Gemini Nano Banana 2.1 is an upgraded multimodal reasoning image model for production-grade image generation and editing, with stronger prompt adherence, multi-reference editing, and improved visual fidelity. It understands text, images, video, and PDF inputs, supports interleaved text and image generation, and can reason over complex spatial and compositional instructions before generating images. The model also supports grounding with Google Search and Google Image Search for better long-tail entity recognition, visual understanding, and output accuracy.

Google: Gemini 3.8 Flash

Gemini 3.8 Flash is Google’s most intelligent workhorse model yet, delivering major gains over 3.7 Flash in software engineering, agentic workflows, and multi-step reasoning for specialized domains. It approaches the quality of higher-cost frontier models while still offering configurable effort levels for balancing performance and token efficiency.

Google: Gemini 3.7 Flash

Gemini 3.7 Flash is Google’s efficient multimodal model designed for coding and agentic workflows. It improves code generation, web application development, tool use, and reliability in complex multi-step tasks while supporting text, image, audio, and video inputs. With a 1-million-token context window, up to 64,000 tokens of output, and adjustable reasoning levels, it is well suited for coding agents, enterprise automation, complex document analysis, and large-scale multimodal applications.

Google: Gemini 3.5 Flash Lite

Gemini 3.5 Flash-Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.