Gemini 3.1 Pro API 是 Google DeepMind 开发的最新通用大语言模型,旨在兼顾高速响应与深度逻辑。它赋能开发者构建高阶智能体,在代码编写、创意写作和跨模态分析方面实现业界领先的精准度。

Pricing: Input 100 credits / 1M tokens (≈ $0.50), Output 700 credits / 1M tokens (≈ $3.50). Both are ~70–75% cheaper than official pricing. High-tier top-ups (+10% bonus) bring effective pricing down to ~$0.45 for Input 1M tokens and ~$3.15 for Output 1M tokens.
gemini-3.1-pro-openai

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Grounding with Google Search
Source:Google Search
Thinking process
Reasoning effort

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README

Complete guide to using gemini-3.1-pro

Kie.ai 高性价比 Gemini 3.1 Pro API

展示界面组件的首屏演示图
谷歌 Gemini 3.1 Pro API:赋能创意界面工程
基准测试Gemini 3.1 ProGemini 3 ProSonnet 4.6Opus 4.6GPT-5.2GPT-5.3-Codex
Humanity’s Last Exam (No tools)44.40%37.50%33.20%40.00%34.50%—
Humanity’s Last Exam (Search + Code)51.40%45.80%49.00%53.10%45.50%—
ARC-AGI-277.10%31.10%58.30%68.80%52.90%—
GPQA Diamond94.30%91.90%89.90%91.30%92.40%—
Terminal-Bench 2.068.50%56.90%59.10%65.40%54.00%64.70%
SWE-Bench Verified80.60%76.20%79.60%80.80%80.00%—
SWE-Bench Pro (Public)54.20%43.30%——55.60%56.80%
LiveCodeBench Pro (Elo)28872439——2393—
SciCode59%56%47%52%52%—
APEX-Agents33.50%18.40%—29.80%23.00%—
GDPval-AA Elo13171195163316061462—
τ2-bench (Retail)90.80%85.30%91.70%91.90%82.00%—
τ2-bench (Telecom)99.30%98.00%97.90%99.30%98.70%—
MCP Atlas69.20%54.10%61.30%59.50%60.60%—
BrowseComp85.90%59.20%74.70%84.00%65.80%—
MMMU Pro80.50%81.00%74.50%73.90%79.50%—
MMMLU92.60%91.80%89.30%91.10%89.60%—
MRCR v2 (128k avg)84.90%77.00%84.90%84.00%83.80%—
MRCR v2 (1M pointwise)26.30%26.30%Not supportedNot supportedNot supported—
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Affordable Gemini 3.1 Pro API pricing on Kie.ai is structured to support both experimentation and large-scale production workloads. Usage-based billing ensures predictable cost control, while efficient token management allows teams to optimize spending without sacrificing reasoning performance. Gemini 3.1 Pro API pricing is designed to remain sustainable as application demands grow.

Gemini 3.1 Pro API documentation on Kie.ai provides clear technical references covering authentication, request schemas, structured outputs, function calling, and deployment workflows. Well-organized developer guides and parameter specifications reduce integration time and support advanced system design. Gemini 3.1 Pro API documentation ensures consistent implementation across development and production environments.

Kie.ai provides access to a rich Gemini API model series in addition to Gemini 3.1 Pro API. This enables developers to select models based on reasoning depth, latency requirements, multimodal capabilities, and workload complexity. Managing a diverse Gemini API model series within a unified platform simplifies architectural decisions and supports multi-model deployment strategies.

Continuous 24/7 support ensures stable integration and reliable production deployment of Gemini 3.1 Pro API. Kie.ai provides assistance for implementation issues, architecture optimization, and performance troubleshooting. Dedicated support reduces operational risk and maintains consistent service availability for enterprise-grade applications.