Gemini 2.5 Pro

Name: Gemini 2.5 Pro
Brand: Google DeepMind
SKU: gemini-2-5-pro
Price: 1.5 USD
Availability: InStock

Text și chatVersiune anterioarăDisponibil

de Google DeepMindgemini-2-5-pro

Google's latest thinking model. Excels at reasoning, coding, math, and science with massive context window.

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Preț · 1M intrare/ieșire: 1,50 USD / 12,00 USD
Context: 1.000.000 tokeni
Ieșire max.: 65.536 tokeni
Intrare → ieșire: Text → Text
Dezvoltator: Google DeepMind
Actualizat: 23 septembrie 2026

Aceasta este o versiune mai veche a modelului.

Playground

Încearcă Gemini 2.5 Pro

Chat

1,50 USD/1M in

Trimite un mesaj. Răspunsul sosește complet când modelul termină (fără streaming).

Lungimea max. a răspunsului (tokeni)

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maximum 0,0123 USD · 1,23 credite rezervate

Se factureaza tokenurile efectiv utilizate; partea nefolosita a rezervării este rambursată.

Nou aici?

10 credite gratuite (0,10 USD) când te înregistrezi cu Google

Utilizabil 24 ore după înregistrare, până la 5 rulări pe zi și maximum 2 credite pe rulare. Alte metode de conectare încep fără credite. Suficient pentru 8 rulări ale acestui model.

Despre Gemini 2.5 Pro

Pe scurtDin 23 septembrie 2026

Gemini 2.5 Pro este un model de Google DeepMind din categoria Text și chat. Pe Railwail, Gemini 2.5 Pro costă 1,50 USD per 1M tokeni de intrare și 12,00 USD per 1M tokeni de ieșire. Fereastra de context conține 1.000.000 token-uri, iar un răspuns poate fi lung de până la 65.536 token-uri.

Fundal

Despre Google DeepMind

Fondat 2010 · Mountain View, USA / London, UK

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.

Vizitează Google DeepMind

Arhitectură

Sparse Mixture-of-Experts Transformer (natively multimodal, reasoning)

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.

Parametri: Undisclosed (sparse MoE, total parameters in the hundreds of billions, active per-token undisclosed)
Context: 1.048.576 tokeni

Capabilități

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.

Antrenament & licență

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.

Licență: Proprietary commercial license via Google AI Studio, Vertex AI and the Gemini app. Commercial use permitted under Google Cloud terms.

Teste de siguranță: Evaluated under Google DeepMind's Frontier Safety Framework v2 covering CBRN, cyber, persuasion and ML R&D risks, with internal red teams and external evaluators.

Limitări cunoscute

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

Lucrări de cercetare

Prețuri

Prețuri în dolari americani. Utilizarea se percepe din credite prepay.

Intrare	1,50 USD / 1M token-uri
Ieșire	12,00 USD / 1M token-uri
Intrare (prompt-uri peste 200.000 token-uri)	3,00 USD / 1M token-uri
Ieșire (prompt-uri peste 200.000 token-uri)	18,00 USD / 1M token-uri

Se facturează token-urile pe care le folosește efectiv fiecare cerere.
1 credit = 0,01 USD

Calculator de costuri

Calculator de preț

Token-uri de intrare

/ cerere

Token-uri de ieșire

/ cerere

Cereri

Total

0,75 USD

75 credite

Pe cerere

0,0075 USD · 0,75 credite

Fiecare cerere este rotunjită la 0,01 credite.

API

Apelează Gemini 2.5 Pro cu cheia ta API Railwail. Folosește acest ID de model în cerere:

gemini-2-5-proDocumentația API Obține o cheie API

curl https://railwail.com/api/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2-5-pro",
    "messages": [
      {
        "role": "user",
        "content": "Explain what a vector database is in two sentences."
      }
    ],
    "max_tokens": 1024
  }'

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["RAILWAIL_API_KEY"],
    base_url="https://railwail.com/api/v1",
)

completion = client.chat.completions.create(
    model="gemini-2-5-pro",
    messages=[
        {
            "role": "user",
            "content": "Explain what a vector database is in two sentences.",
        },
    ],
    max_tokens=1024,
)

print(completion.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.RAILWAIL_API_KEY,
  baseURL: "https://railwail.com/api/v1",
});

const completion = await client.chat.completions.create({
  model: "gemini-2-5-pro",
  messages: [
    {
      role: "user",
      content: "Explain what a vector database is in two sentences."
    }
  ],
  max_tokens: 1024
});

console.log(completion.choices[0].message.content);

// npm install railwail
import railwail from "railwail";

const rw = railwail(process.env.RAILWAIL_API_KEY);

const res = await rw.chat("gemini-2-5-pro", [
  { role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });

console.log(res.choices[0].message.content);

Setează cheia ca RAILWAIL_API_KEYCreează cheie API

Specificații

ID model: gemini-2-5-pro
Dezvoltator: Google DeepMind
Categorie: Text și chat
Intrare: Text
Ieșire: Text
Fereastră de context: 1.000.000 tokeni
Ieșire max.: 65.536 tokeni
Facturare: După utilizare (tokeni sau timp GPU)
Ciclu de viață: Versiune anterioară
Dimensiune model: Undisclosed (sparse MoE, total parameters in the hundreds of billions, active per-token undisclosed)
Licență: Proprietary commercial license via Google AI Studio, Vertex AI and the Gemini app. Commercial use permitted under Google Cloud terms.
Intrare catalog actualizată: 23 septembrie 2026

Etichete

reasoning
coding
multimodal

Indicații de exemplu

Exemple din catalogul Railwail. Nu au fost generate live pe această pagină.

Scientific Analysis
Explain CRISPR-Cas9 gene editing: how it works, current medical applications, and ethical considerations
Arată răspunsul exemplu
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.
Long Context Analysis
I have a 200-page legal contract. Identify all clauses related to intellectual property ownership, data retention, and termination conditions.
Arată răspunsul exemplu
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.

Cazuri de utilizare

Pentru ce se folosește

Long-video and long-PDF analysis
Scientific research and literature review
Coding agents with Deep Think
Search-grounded chatbots
Multimodal data extraction
Enterprise document understanding

Ghiduri conexe

Best Large Language Models

Toate modelele din Text și chat

Întrebări frecvente

Ce este Gemini 2.5 Pro?

Gemini 2.5 Pro este un model de Google DeepMind din categoria Text și chat. Pe Railwail îl poți apela cu o cheie API prin Railwail API.

Cât costă Gemini 2.5 Pro pe Railwail?

Pe Railwail, Gemini 2.5 Pro costă 1,50 USD per 1M tokeni de intrare și 12,00 USD per 1M tokeni de ieșire. Ți se percepe taxa pentru ceea ce fiecare cerere folosește efectiv. Utilizarea se plătește din credite prepay; 1 credit egal cu 0,01 USD.

Care este fereastra de context a Gemini 2.5 Pro?

Fereastra de context a Gemini 2.5 Pro conține 1.000.000 token-uri. Un răspuns poate fi lung de până la 65.536 token-uri.

Cât de rapid este Gemini 2.5 Pro?

Nu sunt suficiente rulări măsurate ale Gemini 2.5 Pro pe Railwail încă pentru a indica un timp de rulare. Depinde de intrare, de setări și de sarcina la furnizor.

Este Gemini 2.5 Pro mai bun decât Claude Fable 5.1?

Depinde de sarcină. Gemini 2.5 Pro (Google DeepMind) și Claude Fable 5.1 (Anthropic) sunt ambele modele din categoria Text și chat. Pagina de comparație arată prețurile și specificațiile lor una lângă alta.

Compară Gemini 2.5 Pro și Claude Fable 5.1

Cum folosesc Gemini 2.5 Pro prin API?

Creează o cheie Railwail API și trimite cererea cu ID-ul modelului gemini-2-5-pro. Exemple de cod pentru curl, Python și JavaScript sunt în secțiunea API a acestei pagini.

Modele comparabile

Toate din această categorie

Claude Fable 5.1Anthropic
Anthropic's model for the most demanding reasoning and long-horizon agentic work. 1M-token context window, up to 128K output tokens, adaptive thinking that is always on.
12,00 USD/1M in
700 % mai scump pe unitate
Compară Gemini 2.5 Pro vs. Claude Fable 5.1
Claude Opus 4.8Anthropic
The most capable model of Anthropic's Opus 4 series. State of the art on long-horizon agentic work, coding and knowledge tasks, with a 1M-token context window at standard pricing.
6,00 USD/1M in
300 % mai scump pe unitate
Compară Gemini 2.5 Pro vs. Claude Opus 4.8
Claude Opus 5.5Anthropic
Anthropic's current Opus model for long-running agentic coding and knowledge work. 1M-token context window, up to 128K output tokens, adaptive thinking that is always on.
4,80 USD/1M in
220 % mai scump pe unitate
Compară Gemini 2.5 Pro vs. Claude Opus 5.5

Folosește Gemini 2.5 Pro prin API

O cheie API pentru fiecare model pe Railwail. Utilizarea se percepe din credite prepay, 1 credit = 0,01 USD.

Obține cheie API Vizualizează toate modelele