Google

Gemini 3.5 Flash is a Flash model in Google's Gemini 3 series, optimized for real-world tasks at higher speed and lower cost. It supports thinking. It takes text, image, video, audio and PDF input and produces text output, with a 1M-token context window and up to 65K output tokens.

Gemma 4 26B A4B Uncensored is a community fine-tune of Google DeepMind's Gemma 4 26B A4B, modified to reduce refusals. The base model is a Mixture-of-Experts model with 25.2B total and 3.8B active parameters; this variant takes text input and produces text output.

Gemma 4 31B is the dense instruction-tuned model in Google DeepMind's open-weight Gemma 4 family, with about 30.7B parameters. It takes text and image input and produces text output, with a 256K-token context window, configurable thinking, native function calling and pretraining on over 140 languages.

Gemma 3 27B Instruct is the 27-billion-parameter instruction-tuned model in Google DeepMind's Gemma 3 family of open-weight multimodal models. It takes text and image input and produces text output, with a 128K-token context window and support for over 140 languages, for tasks such as chat, summarization, question answering and image understanding.

Gemma 4 26B A4B Instruct is the Mixture-of-Experts model in Google DeepMind's open-weight Gemma 4 family, with 25.2B total and 3.8B active parameters per token. It takes text and image input and produces text output, with a 256K-token context window, configurable thinking and native function calling.

Gemma 4 Uncensored is an uncensored variant of Google Gemma 4 26B, a Mixture-of-Experts model with 26B total parameters and only 4B active per token. Fine-tuned for uncensored chat without content filtering, it supports 256K context, coding, and general-purpose conversation.

Gemma 3 12B Instruct is the 12-billion-parameter instruction-tuned model in Google DeepMind's Gemma 3 family of open-weight multimodal models. It takes text and image input and produces text output, with a 128K-token context window and support for over 140 languages, for tasks such as chat, summarization, question answering and image understanding.

Gemma 3 4B Instruct is the 4-billion-parameter instruction-tuned model in Google DeepMind's Gemma 3 family of open-weight multimodal models. It takes text and image input and produces text output, with a 128K-token context window and support for over 140 languages, for tasks such as chat, summarization, question answering and image understanding.

Gemma 4 31B Instruct Turbo is a faster serving variant of Gemma 4 31B, the dense instruction-tuned model in Google DeepMind's open-weight Gemma 4 family. The base model takes text and image input and produces text output, with a 256K-token context window, configurable thinking and native function calling.

Gemma 4 12B Instruct is the instruction-tuned 12B model in Google DeepMind's Gemma 4 family of open models. It is a dense 11.95B-parameter multimodal model with configurable thinking modes, native function calling, and support for over 140 languages.

Gemma 4 31B Instruct NVFP4 is a 4-bit NVFP4 quantization of Gemma 4 31B IT, Google DeepMind's 30.7B-parameter dense open model, with both weights and activations quantized. It supports text and image input, configurable thinking, and function calling.

Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi-turn chat, and coding assistance. It delivers near Pro level reasoning with substantially lower latency.

Gemini 3.1 Pro Preview is the preview release of Google's Gemini 3.1 Pro, a reasoning model for software engineering and agentic workflows that need precise tool use. It refines the Gemini 3 Pro series with better thinking, improved token efficiency and more grounded, factually consistent answers. It takes text, image, video, audio and PDF input and produces text output, with a 1M-token context window and up to 65K output tokens.

Gemini 3.5 Flash-Lite is the fastest, most cost-efficient Gemini 3.5 model with 1M context, ideal for everyday questions, summarization, and lightweight coding tasks.

Gemini 3.6 Flash is a Flash model in Google's Gemini 3 series designed for agentic work, with strengths in code generation, agentic execution and spatial reasoning. It suits fast agentic loops with complex coding cycles. It takes text, image, video, audio and PDF input and produces text output, with a 1M-token context window and up to 65K output tokens.

Gemini 3.7 Flash is a Flash model in Google's Gemini 3 series of natively multimodal reasoning models, built as a workhorse for coding and agentic work. It improves on Gemini 3.6 Flash in coding and web development, supports low, medium and high thinking levels, and has a 1M-token context window with up to 65K output tokens.

Gemini 3.8 Flash is a Flash model in Google's Gemini 3 series, engineered for long-horizon software engineering, autonomous agents and complex enterprise workflows at Flash-level speed and cost. It takes text, image, video, audio and PDF input and produces text output, with a 1M-token context window, up to 65K output tokens and low, medium and high thinking levels.

Gemini 4 Argon is Google's frontier model for complex workflows across software engineering, enterprise knowledge work, and cybersecurity defense, with a unified 1M token context window and tunable thinking.

Gemini 2.5 Flash is Google's thinking model built for price-performance, suited to large-scale processing, low-latency, high-volume tasks and agentic use cases. It takes text, image, video and audio input and produces text output, with a 1M-token context window and up to 65K output tokens.

Gemini 3.1 Flash-Lite is Google's low-latency, cost-effective multimodal model for high-frequency, lightweight tasks such as high-volume agentic workflows and simple data extraction. It takes text, image, video, audio and PDF input and produces text output, with a 1M-token context window, up to 65K output tokens and thinking support.

Gemma 4 31B Instruct Ultra is a speed-optimized serving variant of Gemma 4 31B, the dense instruction-tuned model in Google DeepMind's open-weight Gemma 4 family. The base model takes text and image input and produces text output, with a 256K-token context window, configurable thinking and native function calling.

Gemini 2.5 Flash-Lite is Google's cost-efficient multimodal model in the Gemini 2.5 family, built for high-frequency, lightweight tasks such as high-volume classification and simple data extraction. It takes text, image, video, audio and PDF input and produces text output, with a 1M-token context window and thinking support.

Gemini 2.5 Pro is Google's thinking model for reasoning over complex problems in code, math and STEM. It can analyze large datasets, codebases and documents using long context, taking text, image, video, audio and PDF input and producing text output, with a 1M-token context window and up to 65K output tokens.

Free access to Gemma 4 26B A4B on limited shared capacity. Anonymous route; account opt-in required.

Gemini 3.1 Flash TTS is Google's low-latency text-to-speech model that turns text into natural, expressive speech in more than 70 languages. It supports native multi-speaker dialogue and audio tags written into the text to steer style, pace and delivery, and its audio carries a SynthID watermark.

Gemini Embedding 2 is Google's natively multimodal embedding model, in preview. It maps text, images, video, audio and PDF documents into a single embedding space across more than 100 languages, accepting up to 8,192 text tokens, with 3,072-dimensional output that can be shortened through Matryoshka Representation Learning.

Nano Banana 2 Lite (Gemini 3.1 Flash-Lite Image) is the speed- and cost-focused model in Google DeepMind's Nano Banana image family, built for high-volume generation and editing. This variant generates images from a text prompt.