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Google: Gemini 1.5 Pro

Google: Gemini 1.5 Pro

Google’s High-Context, Multimodal AI Model for Scalable API Integration

Context: 1 000 000 tokens
Output: 8 000 tokens
Modality:
Text
Image
Audio
Video
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Frame

Multimodal, Long-Context LLM for Real-Time Applications via API
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Gemini 1.5 Pro is a powerful multimodal large language model from Google DeepMind, designed for real-time reasoning, long-context understanding, and scalable AI application development. As the mid-tier model in the Gemini 1.5 series, it bridges the gap between lightweight assistants and research-grade frontier models.

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Available via API and natively integrated into Google Cloud and AnyAPI.ai platforms, Gemini 1.5 Pro supports complex logic, multilingual content generation, and image+text interaction for developers and enterprises alike.
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Key Features of Gemini 1.5 Pro
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Up to 1 Million Token Context

Gemini 1.5 Pro supports extended contexts of up to 1 million tokens in specialized configurations (default: 128k), enabling in-depth document reasoning, codebase summarization, and knowledge threading.
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Multimodal Input Support (Text + Images)

Natively processes images alongside text, making it ideal for visual Q&A, screenshot interpretation, and document parsing.
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High-Performance Reasoning and Code Support

Gemini 1.5 Pro excels at multi-step logic, chain-of-thought reasoning, and multilingual code generation across Python, TypeScript, and Go.
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Low Latency for Real-Time Inference

Optimized for fast response times even on large prompts, making it production-ready for dynamic user-facing AI tools.
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Multilingual and Global Usability

Supports 30+ languages, enabling global app deployment and multilingual content operations.
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Use Cases for Gemini 1.5 Pro
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Visual and Multimodal Assistants

Build image-aware chatbots that accept screenshots, charts, or diagrams and provide intelligent, grounded answers.
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Document Intelligence and Summarization

Ingest multi-document workflows, technical manuals, or financial PDFs and output executive summaries, structured data, or action plans.
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AI Developer Assistants

Enable AI pair programming features in IDEs and browser-based tools with fast, context-aware completions and refactoring suggestions.
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Enterprise RAG Pipelines

Pair with vector search for real-time retrieval-augmented generation across massive knowledge corpora.
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Multilingual Customer Automation

Use Gemini 1.5 Pro for international helpdesk support, content localization, and translation-aware automation.


Why Use Gemini 1.5 Pro via AnyAPI.ai
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No Google Cloud Setup Required

Access Gemini 1.5 Pro directly via AnyAPI.ai—no GCP billing, provisioning, or identity configuration needed.
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Unified Access to Top LLMs

Use Gemini alongside GPT, Claude, and Mistral in one platform with a shared API and SDK structure.
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Usage-Based Billing for Flexibility

Only pay for what you use—Gemini 1.5 Pro is accessible for startups, enterprise prototyping, and scale-up deployments.
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Production-Ready Developer Infrastructure

Includes logging, latency tracking, version control, and environment separation for production AI workloads.
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Faster Provisioning Than OpenRouter/AIMLAPI

Get instant access with better rate limits, analytics, and onboarding for team-wide deployment.


Use Gemini 1.5 Pro via AnyAPI.ai for Multimodal, Scalable AI
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Gemini 1.5 Pro combines long-context understanding, multimodal input, and multilingual fluency for next-gen AI applications.

Access Gemini 1.5 Pro via AnyAPI.ai and start building powerful AI experiences today.
Sign up, get your API key, and deploy in minutes.

Comparison with other LLMs

Model
Context Window
Multimodal
Latency
Strengths
Model
Google: Gemini 1.5 Pro
Context Window
1mil
Multimodal
Yes
Latency
Fast
Strengths
Visual input, long context, multilingual coding
Get access
Model
Anthropic: Claude 4 Sonnet
Context Window
200
Multimodal
Yes
Latency
Very Fast
Strengths
Speed, alignment, long memory
Get access
Model
OpenAI: GPT-4 Turbo
Context Window
128k
Multimodal
Yes
Latency
Very High
Strengths
Production-scale AI systems
Get access
Model
Google: Gemini 1.5 Flash
Context Window
1m
Multimodal
Yes
Latency
Ultra Fast
Strengths
Chatbots, multimodal UIs, automation agents
Get access
Model
Mistral: Mistral Large
Context Window
128k
Multimodal
No
Latency
Fast
Strengths
Open-weight, cost-efficient, customizable
Get access

Sample code for 

Google: Gemini 1.5 Pro

Python
JavaScript
Curl
import requests

url = "https://api.anyapi.ai/v1/chat/completions"

payload = {
    "stream": False,
    "tool_choice": "auto",
    "logprobs": False,
    "model": "gemini-pro-1.5",
    "messages": [
        {
            "content": [
                {
                    "type": "text",
                    "text": "Hello"
                },
                {
                    "image_url": {
                        "detail": "auto",
                        "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                    },
                    "type": "image_url"
                }
            ],
            "role": "user"
        }
    ]
}
headers = {
    "Authorization": "Bearer AnyAPI_API_KEY",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
import requests url = "https://api.anyapi.ai/v1/chat/completions" payload = { "stream": False, "tool_choice": "auto", "logprobs": False, "model": "gemini-pro-1.5", "messages": [ { "content": [ { "type": "text", "text": "Hello" }, { "image_url": { "detail": "auto", "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }, "type": "image_url" } ], "role": "user" } ] } headers = { "Authorization": "Bearer AnyAPI_API_KEY", "Content-Type": "application/json" } response = requests.post(url, json=payload, headers=headers) print(response.json())
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const url = 'https://api.anyapi.ai/v1/chat/completions';
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer AnyAPI_API_KEY', 'Content-Type': 'application/json'},
  body: '{"stream":false,"tool_choice":"auto","logprobs":false,"model":"gemini-pro-1.5","messages":[{"content":[{"type":"text","text":"Hello"},{"image_url":{"detail":"auto","url":"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"},"type":"image_url"}],"role":"user"}]}'
};

try {
  const response = await fetch(url, options);
  const data = await response.json();
  console.log(data);
} catch (error) {
  console.error(error);
}
const url = 'https://api.anyapi.ai/v1/chat/completions'; const options = { method: 'POST', headers: {Authorization: 'Bearer AnyAPI_API_KEY', 'Content-Type': 'application/json'}, body: '{"stream":false,"tool_choice":"auto","logprobs":false,"model":"gemini-pro-1.5","messages":[{"content":[{"type":"text","text":"Hello"},{"image_url":{"detail":"auto","url":"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"},"type":"image_url"}],"role":"user"}]}' }; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); }
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Code is copied
curl --request POST \
  --url https://api.anyapi.ai/v1/chat/completions \
  --header 'Authorization: Bearer AnyAPI_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
  "stream": false,
  "tool_choice": "auto",
  "logprobs": false,
  "model": "gemini-pro-1.5",
  "messages": [
    {
      "content": [
        {
          "type": "text",
          "text": "Hello"
        },
        {
          "image_url": {
            "detail": "auto",
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
          },
          "type": "image_url"
        }
      ],
      "role": "user"
    }
  ]
}'
curl --request POST \ --url https://api.anyapi.ai/v1/chat/completions \ --header 'Authorization: Bearer AnyAPI_API_KEY' \ --header 'Content-Type: application/json' \ --data '{ "stream": false, "tool_choice": "auto", "logprobs": false, "model": "gemini-pro-1.5", "messages": [ { "content": [ { "type": "text", "text": "Hello" }, { "image_url": { "detail": "auto", "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }, "type": "image_url" } ], "role": "user" } ] }'
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FAQs

Answers to common questions about integrating and using this AI model via AnyAPI.ai

Is Gemini 1.5 Pro the same as Gemini Advanced?

Gemini 1.5 Pro powers Gemini Advanced but is also available as an API model via third-party providers like AnyAPI.ai.

Can Gemini 1.5 Pro process images and screenshots?

Yes. It supports text+image input for multimodal reasoning.

How does Gemini 1.5 Pro compare to GPT-4 Turbo?

Gemini 1.5 Pro performs similarly on reasoning and code, but adds visual input and extended context capabilities.

Does it support multilingual output?

Yes. Gemini 1.5 Pro can generate and reason in 30+ languages.

Can I access Gemini 1.5 Pro without using Google Cloud?

Yes. AnyAPI.ai provides direct access without Google Cloud setup.

Still have questions?

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