Gemini 2.5 Pro
Google's latest thinking model. Excels at reasoning, coding, math, and science with massive context window.
Gemini 2.5 Pro is text & chat AI model from Google DeepMind, priced at €12.50 per 1M input tokens with a 1M tokens context window.
0.7
Examples
See what Gemini 2.5 Pro can generate
Explain CRISPR-Cas9 gene editing: how it works, current medical applications, and ethical considerations
CRISPR-Cas9 works like molecular scissors guided by a GPS. A guide RNA is designed to match a specific DNA sequence; the Cas9 protein then cuts the DNA at that exact location, allowing scientists to delete, repair, or insert genetic material. Current medical applications include sickle cell disease treatment (Casgevy, approved 2023), where patients' stem cells are edited ex vivo to produce functional hemoglobin. Clinical trials are underway for certain cancers, hereditary blindness, and HIV resistance. Ethical considerations center on germline editing (changes passed to future generations), equitable access to expensive therapies, and the slippery slope toward 'designer babies'—most scientists support a moratorium on heritable human genome editing while governance frameworks catch up.
I have a 200-page legal contract. Identify all clauses related to intellectual property ownership, data retention, and termination conditions.
I can process your entire 200-page contract within my context window. Here's what I would systematically extract: 1) IP Ownership clauses: Look for sections titled 'Intellectual Property,' 'Work Product,' or 'Ownership of Deliverables'—these define who owns code, designs, and inventions created during the engagement. 2) Data Retention: Sections covering 'Data Handling,' 'Confidentiality,' or 'Information Security' typically specify how long each party retains data post-termination, deletion timelines, and compliance with regulations like GDPR. 3) Termination Conditions: Usually in a dedicated 'Termination' section, covering for-cause vs. for-convenience termination, notice periods, cure periods for breaches, and post-termination obligations. Upload the document and I'll provide exact clause references, page numbers, and a summary of each relevant provision with any potential conflicts between sections.
Pricing
API Integration
Use our OpenAI-compatible API to integrate Gemini 2.5 Pro into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
// Simple — just pass a string
const reply = await rw.run("gemini-2-5-pro", "Hello! What can you do?");
console.log(reply);
// With message history
const reply2 = await rw.run("gemini-2-5-pro", [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain quantum computing simply." },
]);
console.log(reply2);
// Full response with usage info
const res = await rw.chat("gemini-2-5-pro", [
{ role: "user", content: "Hello!" },
], { temperature: 0.7, max_tokens: 500 });
console.log(res.choices[0].message.content);
console.log(res.usage);Deep dive — Google DeepMind's Gemini 2.5 Pro
Google DeepMind is the merged AI research organisation formed in April 2023 by combining Google Brain (founded inside Google in 2011) with DeepMind (founded in London in 2010 by Demis Hassabis, Shane Legg and Mustafa Suleyman, acquired by Google in 2014). Demis Hassabis leads the unit as CEO. DeepMind authored seminal papers including 'Attention Is All You Need' (Google Brain, 2017), AlphaGo (2016), AlphaFold (2018-2021, awarded the 2024 Nobel Prize in Chemistry), AlphaZero, Chinchilla scaling laws and the Gemini Technical Report. The Gemini family launched in December 2023 (Ultra, Pro, Nano), followed by Gemini 1.5 Pro with 1M+ context and the Mixture-of-Experts architecture in early 2024, Gemini 2.0 Flash (December 2024) and Gemini 2.5 Pro (released March 2025, generally available May 2025) which introduced a built-in 'Deep Think' reasoning mode. Google DeepMind also ships Imagen, Veo, Lyria, NotebookLM and powers AI features across Google Search, Workspace and Android.
Visit Google DeepMind →Gemini 2.5 Pro is Google DeepMind's flagship reasoning model released as preview in March 2025 and generally available in May 2025. It is a natively multimodal Sparse Mixture-of-Experts (MoE) Transformer that ingests text, image, audio and video tokens through a shared embedding space, building on the architecture introduced in Gemini 1.5 Pro. Pretraining used Google's TPU v5p infrastructure on a multi-trillion-token corpus mixing web text, code, books, scientific papers, image-text pairs, audio and YouTube video frames, with a knowledge cutoff of January 2025. Post-training combined supervised fine-tuning, RLHF and reinforcement learning against verifiable rewards for math and code, plus a new 'Deep Think' training stage that teaches the model to allocate test-time thinking budgets and emit long internal chains-of-thought before the final answer. Deep Think is exposed to developers as a toggle and was the headline capability at launch, pushing Gemini 2.5 Pro to the top of the Chatbot Arena leaderboard for the first time for Google. The model supports a 1,048,576-token context window with native handling of long PDFs, hour-long videos and full code repositories. Tool use, function calling, structured output and grounding with Google Search are first-class. Safety training included red-teaming under Google's Frontier Safety Framework.
- Parameters
- Undisclosed (sparse MoE, total parameters in the hundreds of billions, active per-token undisclosed)
- Context
- 1.0M tokens
- 1,048,576 token context window (~1M tokens) with native long-video and long-audio support
- Built-in Deep Think reasoning mode with adjustable thinking budget
- Natively multimodal: text, image, audio and video in a single pass
- Top scores on GPQA Diamond, AIME 2025 and Humanity's Last Exam
- Strong coding performance on SWE-bench Verified and LiveCodeBench
- Function calling, JSON schema, parallel tool calls
- Grounding with Google Search built into the API
- Native execution of code via the Code Execution tool
- Cross-lingual reasoning across 100+ languages
- Available via Vertex AI, AI Studio, and the Gemini app
- Best for: scientific reasoning, long-document and long-video analysis, coding, agentic workflows.
Pretrained on a multi-trillion-token mixture of web text, code, books, scientific papers, licensed third-party text, audio waveforms, image-text pairs and video frames. Knowledge cutoff is January 2025. Post-training uses supervised fine-tuning, RLHF, RL against verifiable rewards and Deep Think reasoning training.
License: Proprietary commercial license via Google AI Studio, Vertex AI and the Gemini app. Commercial use permitted under Google Cloud terms.
Known limitations
- Deep Think adds significant latency and token cost
- Long context recall quality degrades beyond ~500K tokens for some tasks
- Vision occasionally misreads dense tables and handwriting
- Knowledge cutoff January 2025
- Region availability varies and is not yet in all EU regions for some features
Frequently asked questions
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