2M Token Context Recall
Analyze 50+ contracts or massive codebases with near-perfect retrieval accuracy across 2 million tokens.
Gemini 2.5 Pro
Gemini 2.5 Pro API offers a massive 2-million-token context window for deep analysis of video, audio, and large codebases. This multimodal model from Google excels at complex reasoning and high-recall retrieval tasks for enterprise needs.
Esempi di utilizzo dell’API
curl --request POST "https://gptproto.com/v1/chat/completions" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "gemini-2.5-pro",
"messages": [
{
"role": "user",
"content": "Hello"
}
]
}'Prezzi Gemini 2.5 Pro
Chat, agenti di coding e lavoro sui documenti. Prezzi per 1M di token: input, input memorizzato nella cache e output vengono fatturati separatamente. GPTProto costa il 40% in meno rispetto alle tariffe ufficiali.
| Scenario | Listino ufficiale Google | OpenRouter | GPTProto | Risparmi al mese |
|---|---|---|---|---|
| Personale10M token/mese (4.8M nella cache) | $24.60 | $25.95 | $14.76 | −$9.84≈ $118.08 / anno |
| Team100M token/mese (48M nella cache) | $246.00 | $259.53 | $147.60 | −$98.40≈ $1180.80 / anno |
| Aziendale500M token/mese (240M nella cache) | $1230.00 | $1297.65 | $738.00 | −$492.00≈ $5904.00 / anno |
Risparmia $0.00 / mese
Risparmio annuale ≈ $0.00 · pagamento a consumo
Modelli correlati
Tutti i modelli
Gemini 2.5 ProAttuale
Google · 1.05M context · $0.75/M input · $6/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Modello
Prezzo: GPTProto
vs ufficiale
vs OpenRouter
Contesto
Stabilità
Gemini 2.5 ProAttuale
Google
$0.75 / $6.00per 1M di token
-40%
-43%
1.05M
Gemini 2.5 Pro API Core Features
Unlock advanced intelligence with the Gemini 2.5 Pro API. Explore the standout capabilities that differentiate this model from standard LLMs.
Native Multimodal Reasoning
Interleave video, audio, and text in one prompt for deeper cross-modal understanding and analysis.
Agentic Tool Use
Optimized for complex tool chaining and multi-step workflows with 15% better performance than Gemini 1.5.
Efficient Context Caching
Drastically reduce costs by caching frequently used data, perfect for large technical documentation sets.
Gemini 2.5 Pro API Frequently Asked Questions
Find answers to common questions about implementing the Gemini 2.5 Pro API into your tech stack, including pricing, context window capabilities, and multimodal data privacy standards.
What is the Gemini 2.5 Pro API context window?
The Gemini 2.5 Pro API features a massive 2-million-token context window. This allows the model to process thousands of document pages, hours of video footage, or entire software repositories in a single prompt. It maintains over 99% retrieval accuracy across this entire span, making it an industry leader for long-form data analysis and complex research tasks where high-fidelity recall is absolutely critical for enterprise-grade results.
Does Gemini 2.5 Pro support native video input?
Yes, the Gemini 2.5 Pro API supports native multimodal processing. Unlike older models that use separate encoders, Gemini processes text, images, audio, and video interleaved in a single stream. You can upload up to two hours of video for the model to analyze, allowing for timestamp-specific questions, narrative summaries, and detailed visual auditing without needing to manually transcribe or pre-process your media files beforehand.
How much does the Gemini 2.5 Pro API cost?
Pricing for the Gemini 2.5 Pro API is tiered by context size. For prompts under 128k tokens, input costs $1.25 per million tokens. For larger requests over 128k tokens, the price is $2.50 per million. Output tokens consistently cost $3.75 per million. Through GPTProto.com, you can also utilize context caching, which can reduce your input costs by up to 75% for frequently queried long-form datasets or large technical instruction manuals.
Is the Gemini 2.5 Pro API compatible with OpenAI?
Absolutely. GPTProto.com provides an OpenAI-compatible endpoint for the Gemini 2.5 Pro API. This means developers can migrate existing workflows by simply updating the base URL and model name in their current SDK. Whether you use Python, Node.js, or direct cURL commands, the integration is seamless, allowing you to leverage Gemini's 2M context window and multimodal features without rewriting your entire codebase or backend logic.
How does Gemini 2.5 Pro handle complex coding?
Gemini 2.5 Pro is highly proficient at codebase comprehension. Because it can ingest entire GitHub repositories within its context window, the API provides architectural suggestions, identifies security vulnerabilities, and generates documentation across multiple files simultaneously. While it competes closely with other top-tier models, its ability to see the entire project structure at once gives it a unique advantage in legacy code migration.
Is data sent to the Gemini API used for training?
No. Privacy is a core priority for enterprise users of the Gemini 2.5 Pro API. Data processed through our platform and the official API is not used by Google or GPTProto.com to train underlying models. This ensures that your proprietary code, legal contracts, and sensitive financial documents remain confidential. We also offer enterprise-grade security and compliance features to help you meet strict data residency and security requirements.
further reading
Guide, confronti e aggiornamenti relativi a questo modello.
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