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Gemini 3 Pro Preview

gemini-3-pro-preview

This model improves upon Gemini 2.5 Pro and is catered towards challenging tasks, especially those involving complex reasoning or agentic workflows. Improvements highlighted include use cases for coding, multi-step function calling, planning, reasoning, deep knowledge tasks, and instruction following.

Available at 14 Providers

Provider Source Input Price ($/1M) Output Price ($/1M) Description Free
vercel vercel Input: $2.00 Output: $12.00 This model improves upon Gemini 2.5 Pro and is catered towards challenging tasks, especially those involving complex reasoning or agentic workflows. Improvements highlighted include use cases for coding, multi-step function calling, planning, reasoning, deep knowledge tasks, and instruction following.
githubcopilot models-dev Input: $0.00 Output: $0.00 Provider: GitHub Copilot, Context: 128000, Output Limit: 64000
abacus models-dev Input: $2.00 Output: $12.00 Provider: Abacus, Context: 1000000, Output Limit: 65000
venice models-dev Input: $2.50 Output: $15.00 Provider: Venice AI, Context: 202752, Output Limit: 50688
helicone models-dev Input: $2.00 Output: $12.00 Provider: Helicone, Context: 1048576, Output Limit: 65536
google models-dev Input: $2.00 Output: $12.00 Provider: Google, Context: 1000000, Output Limit: 64000
googlevertex models-dev Input: $2.00 Output: $12.00 Provider: Vertex, Context: 1048576, Output Limit: 65536
zenmux models-dev Input: $2.00 Output: $12.00 Provider: ZenMux, Context: 1048576, Output Limit: 64000
requesty models-dev Input: $2.00 Output: $12.00 Provider: Requesty, Context: 1048576, Output Limit: 65536
aihubmix models-dev Input: $2.00 Output: $12.00 Provider: AIHubMix, Context: 1000000, Output Limit: 65000
vertex litellm Input: $2.00 Output: $12.00 Source: vertex, Context: 1048576
gemini litellm Input: $2.00 Output: $12.00 Source: gemini, Context: 1048576
openrouter openrouter Input: $2.00 Output: $12.00 Gemini 3 Pro is Google’s flagship frontier model for high-precision multimodal reasoning, combining strong performance across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling, see our docs here: https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks. It delivers state-of-the-art benchmark results in general reasoning, STEM problem solving, factual QA, and multimodal understanding, including leading scores on LMArena, GPQA Diamond, MathArena Apex, MMMU-Pro, and Video-MMMU. Interactions emphasize depth and interpretability: the model is designed to infer intent with minimal prompting and produce direct, insight-focused responses. Built for advanced development and agentic workflows, Gemini 3 Pro provides robust tool-calling, long-horizon planning stability, and strong zero-shot generation for complex UI, visualization, and coding tasks. It excels at agentic coding (SWE-Bench Verified, Terminal-Bench 2.0), multimodal analysis, and structured long-form tasks such as research synthesis, planning, and interactive learning experiences. Suitable applications include autonomous agents, coding assistants, multimodal analytics, scientific reasoning, and high-context information processing. Context: 1048576
factoryai factoryai Input: - Output: - -