Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution loops, supporting text, image, video, audio, and PDF inputs. Defaults to medium thinking effort for faster and more cost-efficient responses, with full support for thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs.

Gemini 3.1 Flash Lite is Google's GA high-efficiency multimodal model optimized for low-latency, high-volume workloads. It supports text, image, video, audio, and PDF inputs, and is designed for lightweight agentic workflows, simple data extraction, and applications where responsiveness and API cost are the primary constraints. Supports full thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs. Priced at half the cost of Gemini 3 Flash.

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.

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.

Gemini 3.1 Flash Lite Preview is Google's high-efficiency model optimized for high-volume use cases. It outperforms Gemini 2.5 Flash Lite on overall quality and approaches Gemini 2.5 Flash performance across key capabilities. Improvements span audio input/ASR, RAG snippet ranking, translation, data extraction, and code completion. Supports full thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs. Delivers 2.5x faster Time to First Answer Token and 45% increased output speed compared to 2.5 Flash. Priced at half the cost of Gemini 3 Flash.

Nano Banana 2 (Gemini 3.1 Flash Image Preview) is Google's latest state-of-the-art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced contextual understanding with fast, cost-efficient inference, making complex image generation and iterative edits significantly more accessible.

Gemini 3.1 Pro Preview is Google's frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation of the Gemini 3 series, it combines high-precision reasoning across text, image, video, audio, and code with a 1M-token context window. The 3.1 update introduces measurable gains in SWE benchmarks and real-world coding environments, along with stronger autonomous task execution in structured domains such as finance and spreadsheet-based workflows. Designed for advanced development and agentic systems, it introduces a new medium thinking level to better balance cost, speed, and performance.

Google DeepMind's most advanced music generation model, launched in the Gemini app. First Lyria model with full vocal generation, automatic lyric creation, and multimodal inputs (text, image, video). Produces 30-second tracks with distinct verses, choruses, and bridges. Supports 8 languages for vocal generation. No public API yet, available through the Gemini app and YouTube Dream Track.

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 and tool use performance with substantially lower latency than larger Gemini variants, making it well suited for interactive development, long running agent loops, and collaborative coding tasks. Compared to Gemini 2.5 Flash, it provides broad quality improvements across reasoning, multimodal understanding, and reliability. The model supports a 1M token context window and multimodal inputs including text, images, audio, video, and PDFs, with text output. It includes configurable reasoning via thinking levels (minimal, low, medium, high), structured output, tool use, and automatic context caching. Gemini 3 Flash Preview is optimized for users who want strong reasoning and agentic behavior without the cost or latency of full scale frontier models.

Google DeepMind's production music generation model available via Vertex AI. Generates 32.8-second instrumental clips at 48kHz from text prompts. Supports negative prompts to exclude unwanted elements and deterministic generation via seed parameter. All output is SynthID-watermarked.

Gemini 3 Pro Preview with high reasoning effort enabled. Exposes full chain-of-thought process for enhanced transparency in complex problem-solving across text, code, and multimodal tasks.

Nano Banana Pro (Gemini 3 Pro Image) is Google's state-of-the-art image generation and editing model with resolution options up to 4K. Uses Gemini's advanced reasoning (Thinking) for high-fidelity text rendering and complex instructions.

Gemini 2.5 Flash Preview September 2025 Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter described in the documentation.

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.

Google's Nano Banana (Gemini 2.5 Flash Image) is an image generation and editing model, optimized for fast, high-quality results. Tested on LMArena as 'nano-banana', it quickly outperformed Midjourney and Flux in blind tests.

Gemini 2.5 Flash variant tuned for fast text-to-image generation and simple image edits.

Gemma 3n E2B IT is a multimodal, instruction-tuned model developed by Google DeepMind, designed to operate efficiently at an effective parameter size of 2B while leveraging a 6B architecture. Based on the MatFormer architecture, it supports nested submodels and modular composition via the Mix-and-Match framework. Gemma 3n models are optimized for low-resource deployment, offering 32K context length and strong multilingual and reasoning performance across common benchmarks.

Gemini 2.5 Flash Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.

Imagen 4 Fast trades a bit of quality for significantly improved speed and cost.

Gemini 2.5 Pro is Google's state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs "thinking" capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities. Pricing: $1.25/M input tokens, $10/M output tokens, $5.16/K input images.

Imagen 4 Ultra prioritizes maximum quality over speed and cost for best-in-class generations.

Google's Imagen 4 flagship text-to-image model with excellent quality, detail, and prompt adherence.

Gemini 2.5 Flash May 20th Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Note: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the ":thinking" suffix), the model will explicitly avoid generating thinking tokens. To utilize the thinking capability and receive thinking tokens, you must choose the ":thinking" variant, which will then incur the higher thinking-output pricing. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter.

Gemini 2.5 Flash May 20th Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Note: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the ":thinking" suffix), the model will explicitly avoid generating thinking tokens. To utilize the thinking capability and receive thinking tokens, you must choose the ":thinking" variant, which will then incur the higher thinking-output pricing. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter.

Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs (text, visual data, and audio) enabling diverse tasks such as text generation, speech recognition, translation, and image analysis. Leveraging innovations like Per-Layer Embedding (PLE) caching and the MatFormer architecture, Gemma 3n dynamically manages memory usage and computational load by selectively activating model parameters, significantly reducing runtime resource requirements. This model supports a wide linguistic range (trained in over 140 languages) and features a flexible 32K token context window. Gemma 3n can selectively load parameters, optimizing memory and computational efficiency based on the task or device capabilities, making it well-suited for privacy-focused, offline-capable applications and on-device AI solutions.

Our most advanced reasoning model, capable of solving complex problems. Best for multimodal understanding, reasoning over complex problems, complex prompts, tackling multi-step code, math and STEM problems, coding (especially web development), and analyzing large datasets/codebases/documents with long context. Knowledge cutoff Jan 2025.

Google's state-of-the-art workhorse model, designed for advanced reasoning, coding, mathematics, and scientific tasks. Features hybrid reasoning (thinking on/off) with configurable budgets, balancing quality, cost, and latency.

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling.

Gemini 2.5 Pro Experimental is Google's advanced model with improved multimodal reasoning, long context understanding with 1 million tokens, and specialized video comprehension.

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 96000 tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 12B is the second largest in the family after Gemma 3 27B.

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 131072 tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to Gemma 2.

A faster and cheaper Imagen 3 variant for when speed and cost matter more than maximum quality.

Google's high-quality text-to-image model focused on lighting, detail, and strong visual composition.

Gemini 2.0 Pro builds interactive 3D environments from text descriptions and offers hypothetical reasoning for scientific simulations.

Gemini 2.0 Flash Thinking offers fast reasoning capabilities with an efficient architecture designed for complex multi-step problems.

Gemini 1.5 Pro handles infinite context with 99% retrieval accuracy at 750k tokens via Mixture-of-Experts and generates chapter summaries for 2-hour videos with 92% accuracy.

Google's flagship multimodal model (as of release). Designed for natural language tasks, multi-turn chat, code generation, and understanding image inputs.

PaLM 2 by Google features improved multilingual, reasoning, and coding capabilities. Optimized for chat-based interactions.

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution loops, supporting text, image, video, audio, and PDF inputs. Defaults to medium thinking effort for faster and more cost-efficient responses, with full support for thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs.

Gemini 3.1 Flash Lite is Google's GA high-efficiency multimodal model optimized for low-latency, high-volume workloads. It supports text, image, video, audio, and PDF inputs, and is designed for lightweight agentic workflows, simple data extraction, and applications where responsiveness and API cost are the primary constraints. Supports full thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs. Priced at half the cost of Gemini 3 Flash.

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.

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.

Gemini 3.1 Flash Lite Preview is Google's high-efficiency model optimized for high-volume use cases. It outperforms Gemini 2.5 Flash Lite on overall quality and approaches Gemini 2.5 Flash performance across key capabilities. Improvements span audio input/ASR, RAG snippet ranking, translation, data extraction, and code completion. Supports full thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs. Delivers 2.5x faster Time to First Answer Token and 45% increased output speed compared to 2.5 Flash. Priced at half the cost of Gemini 3 Flash.

Nano Banana 2 (Gemini 3.1 Flash Image Preview) is Google's latest state-of-the-art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced contextual understanding with fast, cost-efficient inference, making complex image generation and iterative edits significantly more accessible.

Gemini 3.1 Pro Preview is Google's frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation of the Gemini 3 series, it combines high-precision reasoning across text, image, video, audio, and code with a 1M-token context window. The 3.1 update introduces measurable gains in SWE benchmarks and real-world coding environments, along with stronger autonomous task execution in structured domains such as finance and spreadsheet-based workflows. Designed for advanced development and agentic systems, it introduces a new medium thinking level to better balance cost, speed, and performance.

Google DeepMind's most advanced music generation model, launched in the Gemini app. First Lyria model with full vocal generation, automatic lyric creation, and multimodal inputs (text, image, video). Produces 30-second tracks with distinct verses, choruses, and bridges. Supports 8 languages for vocal generation. No public API yet, available through the Gemini app and YouTube Dream Track.

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 and tool use performance with substantially lower latency than larger Gemini variants, making it well suited for interactive development, long running agent loops, and collaborative coding tasks. Compared to Gemini 2.5 Flash, it provides broad quality improvements across reasoning, multimodal understanding, and reliability. The model supports a 1M token context window and multimodal inputs including text, images, audio, video, and PDFs, with text output. It includes configurable reasoning via thinking levels (minimal, low, medium, high), structured output, tool use, and automatic context caching. Gemini 3 Flash Preview is optimized for users who want strong reasoning and agentic behavior without the cost or latency of full scale frontier models.

Google DeepMind's production music generation model available via Vertex AI. Generates 32.8-second instrumental clips at 48kHz from text prompts. Supports negative prompts to exclude unwanted elements and deterministic generation via seed parameter. All output is SynthID-watermarked.

Gemini 3 Pro Preview with high reasoning effort enabled. Exposes full chain-of-thought process for enhanced transparency in complex problem-solving across text, code, and multimodal tasks.

Nano Banana Pro (Gemini 3 Pro Image) is Google's state-of-the-art image generation and editing model with resolution options up to 4K. Uses Gemini's advanced reasoning (Thinking) for high-fidelity text rendering and complex instructions.

Gemini 2.5 Flash Preview September 2025 Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter described in the documentation.

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.

Google's Nano Banana (Gemini 2.5 Flash Image) is an image generation and editing model, optimized for fast, high-quality results. Tested on LMArena as 'nano-banana', it quickly outperformed Midjourney and Flux in blind tests.

Gemini 2.5 Flash variant tuned for fast text-to-image generation and simple image edits.

Gemma 3n E2B IT is a multimodal, instruction-tuned model developed by Google DeepMind, designed to operate efficiently at an effective parameter size of 2B while leveraging a 6B architecture. Based on the MatFormer architecture, it supports nested submodels and modular composition via the Mix-and-Match framework. Gemma 3n models are optimized for low-resource deployment, offering 32K context length and strong multilingual and reasoning performance across common benchmarks.

Gemini 2.5 Flash Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.

Imagen 4 Fast trades a bit of quality for significantly improved speed and cost.

Gemini 2.5 Pro is Google's state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs "thinking" capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities. Pricing: $1.25/M input tokens, $10/M output tokens, $5.16/K input images.

Imagen 4 Ultra prioritizes maximum quality over speed and cost for best-in-class generations.

Google's Imagen 4 flagship text-to-image model with excellent quality, detail, and prompt adherence.

Gemini 2.5 Flash May 20th Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Note: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the ":thinking" suffix), the model will explicitly avoid generating thinking tokens. To utilize the thinking capability and receive thinking tokens, you must choose the ":thinking" variant, which will then incur the higher thinking-output pricing. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter.

Gemini 2.5 Flash May 20th Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Note: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the ":thinking" suffix), the model will explicitly avoid generating thinking tokens. To utilize the thinking capability and receive thinking tokens, you must choose the ":thinking" variant, which will then incur the higher thinking-output pricing. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter.

Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs (text, visual data, and audio) enabling diverse tasks such as text generation, speech recognition, translation, and image analysis. Leveraging innovations like Per-Layer Embedding (PLE) caching and the MatFormer architecture, Gemma 3n dynamically manages memory usage and computational load by selectively activating model parameters, significantly reducing runtime resource requirements. This model supports a wide linguistic range (trained in over 140 languages) and features a flexible 32K token context window. Gemma 3n can selectively load parameters, optimizing memory and computational efficiency based on the task or device capabilities, making it well-suited for privacy-focused, offline-capable applications and on-device AI solutions.

Our most advanced reasoning model, capable of solving complex problems. Best for multimodal understanding, reasoning over complex problems, complex prompts, tackling multi-step code, math and STEM problems, coding (especially web development), and analyzing large datasets/codebases/documents with long context. Knowledge cutoff Jan 2025.

Google's state-of-the-art workhorse model, designed for advanced reasoning, coding, mathematics, and scientific tasks. Features hybrid reasoning (thinking on/off) with configurable budgets, balancing quality, cost, and latency.

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling.

Gemini 2.5 Pro Experimental is Google's advanced model with improved multimodal reasoning, long context understanding with 1 million tokens, and specialized video comprehension.

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 96000 tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 12B is the second largest in the family after Gemma 3 27B.

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 131072 tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to Gemma 2.

A faster and cheaper Imagen 3 variant for when speed and cost matter more than maximum quality.

Google's high-quality text-to-image model focused on lighting, detail, and strong visual composition.

Gemini 2.0 Pro builds interactive 3D environments from text descriptions and offers hypothetical reasoning for scientific simulations.

Gemini 2.0 Flash Thinking offers fast reasoning capabilities with an efficient architecture designed for complex multi-step problems.

Gemini 1.5 Pro handles infinite context with 99% retrieval accuracy at 750k tokens via Mixture-of-Experts and generates chapter summaries for 2-hour videos with 92% accuracy.

Google's flagship multimodal model (as of release). Designed for natural language tasks, multi-turn chat, code generation, and understanding image inputs.

PaLM 2 by Google features improved multilingual, reasoning, and coding capabilities. Optimized for chat-based interactions.