Gemini 3.1 Pro

Name: Gemini 3.1 Pro
Brand: Google DeepMind
SKU: gemini-3-1-pro
Price: 2.4 USD
Availability: InStock

MultimodalnoNovoRazpoložljivo

od Google DeepMindgemini-3-1-pro

Google DeepMind's February 2026 flagship. 1M-token (1,048,576) context, native multimodal (text/image/audio/video), Deep Think reasoning.

Preizkusi Pridobi API ključ Primerjaj

Cena · 1M vhod/izhod: 2,40 $ / 14,40 $
Kontekst: 1.048.576 žetonov
Največji izhod: 65.536 žetonov
Vhod → Izhod: Besedilo + Slika + Avdio + Video → Besedilo
Razvijalec: Google DeepMind
Posodobljeno: 24. september 2026

Igrišče

Preizkusi Gemini 3.1 Pro

Klepet

2,40 $/1M vhod

Pošlji sporočilo. Odgovor pride v celoti, ko je model končan (brez pretakanja).

Maks. dolžina odgovora (tokeni)

TemperaturaPrivzeto modela

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največ 0,0148 $ · 1,48 kreditov rezervirano

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O Gemini 3.1 Pro

PovzetekOd 24. september 2026

Gemini 3.1 Pro je model razvijalca Google DeepMind iz kategorije Multimodalno. Na Railwail stane Gemini 3.1 Pro 2,40 $ na 1M vhodnih žetonov in 14,40 $ na 1M izhodnih žetonov. Kontekstno okno vsebuje 1.048.576 žetonov, odgovor pa je lahko dolg do 65.536 žetonov.

Released February 19, 2026, Gemini 3.1 Pro is Google DeepMind's flagship frontier model. Native 1,048,576-token context window, fully multimodal (text, image, audio, video tokens in a single pass), built-in Deep Think reasoning with adjustable thinking budgets. Top scores on GPQA Diamond, AIME, Humanity's Last Exam, and strong coding on SWE-bench. Function calling, JSON schema, Search grounding and Code Execution are first-class. Best for: long-document and long-video analysis, scientific reasoning, agentic workflows.

Ozadje

O Google DeepMind

Ustanovljeno 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 (early 2024), Gemini 2.0 Flash (December 2024), Gemini 2.5 Pro with Deep Think (March/May 2025), Gemini 3 Pro (late 2025), Gemini 3.1 Pro (February 2026) and Gemini 3 Flash (April 2026). Google DeepMind also ships Imagen, Veo, Lyria and NotebookLM and powers AI features across Google Search, Workspace and Android.

Obiščite Google DeepMind

Arhitektura

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

Gemini 3.1 Pro was released February 19, 2026 as Google DeepMind's flagship frontier model. It is a natively multimodal Sparse Mixture-of-Experts Transformer that ingests text, image, audio and video tokens through a shared embedding space, building directly on the Gemini 3 Pro architecture (late 2025) and Gemini 2.5 Pro (early 2025). The input context window is 1,048,576 tokens, the same size as Gemini 2.5 Pro. Pretraining used Google's TPU v6e infrastructure on a multi-trillion-token corpus mixing web text, code, books, scientific papers, image-text pairs, audio waveforms and video frames, with a knowledge cutoff in late 2025. Post-training combined supervised fine-tuning, RLHF, reinforcement learning against verifiable rewards on math and code, and a refreshed 'Deep Think' reasoning stage that teaches the model to allocate test-time thinking budgets and emit long internal chains-of-thought before its final answer. Tool use, function calling, structured output, Search grounding and the Code Execution tool are first-class. Safety training followed Google's Frontier Safety Framework v2.

Parametri: Undisclosed (sparse MoE, total parameters in the hundreds of billions, active per-token undisclosed)
Kontekst: 2.000.000 žetonov

Zmožnosti

1,048,576-token input context window 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 2026 and Humanity's Last Exam
Strong coding performance on SWE-bench Verified and LiveCodeBench
Function calling, JSON schema and parallel tool calls
Search grounding and Code Execution tools built into the API
Cross-lingual reasoning across 100+ languages
Available via Vertex AI, AI Studio and the Gemini app (paid-only since April 2026)
2x batch pricing reduction for large jobs
Best for: long-document and long-video analysis, scientific reasoning, agentic workflows, complex multimodal extraction.

Usposabljanje in licenca

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 in late 2025. Post-training uses supervised fine-tuning, RLHF, RL against verifiable rewards and Deep Think reasoning training.

Licenca: Proprietary commercial license via Google AI Studio, Vertex AI and the Gemini app. Paid-only since April 1, 2026.

Preizkusi varnosti: 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.

Znane omejitve

Deep Think adds significant latency and token cost
Prompts above 200K tokens are billed at 2x input / 1.5x output rates
Long-context recall quality can degrade beyond ~1M tokens for some tasks
Vision occasionally misreads dense tables and handwriting
Region availability varies; not yet generally available in all EU regions

Raziskovalni članki

Cene

Cene v ameriških dolarjih. Uporaba se obračuna iz vnaprej plačanih kreditov.

Vhod	2,40 $ / 1M žetonov
Izhod	14,40 $ / 1M žetonov
Vhod (pozivi nad 200.000 žetoni)	4,80 $ / 1M žetonov
Izhod (pozivi nad 200.000 žetoni)	21,60 $ / 1M žetonov

Obračunani so žetoni, ki jih vsak zahtevek dejansko porabi.
1 kredit = 0,01 $

Kalkulator stroškov

Kalkulator cen

Vhodnih žetonov

/ zapr.

Izhodnih žetonov

/ zapr.

Zahtevki

Skupaj

0,96 $

96 kreditov

Na zahtevek

0,0096 $ · 0,96 kreditov

Vsak zahtevek se zaokroži navzgor na 0,01 kredita.

API

Pokličite Gemini 3.1 Pro s svojim Railwail API ključem. V zahtevku uporabite to ID modela:

gemini-3-1-proDokumentacija API Pridobite API ključ

curl https://railwail.com/api/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3-1-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-3-1-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-3-1-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-3-1-pro", [
  { role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });

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

Nastavite ključ kot RAILWAIL_API_KEYUstvari API ključ

Specifikacije

ID modela: gemini-3-1-pro
Razvijalec: Google DeepMind
Kategorija: Multimodalno
Vhod: Besedilo, Slika, Avdio, Video
Izhod: Besedilo
Kontekstno okno: 1.048.576 žetonov
Maks. izhod: 65.536 žetonov
Obračunavanje: Po porabi (žetoni ali čas GPU)
Velikost modela: Undisclosed (sparse MoE, total parameters in the hundreds of billions, active per-token undisclosed)
Licenca: Proprietary commercial license via Google AI Studio, Vertex AI and the Gemini app. Paid-only since April 1, 2026.
Kataložni vnos posodobljen: 24. september 2026

Vhodne parametre

Vhodi in nastavitve iz vhodne sheme modela. Primer v razdelku API prikazuje, katere od njih API sprejema.

ParameterTipPrivzetoDovoljene vrednosti

promptObvezno
User message
Tip: Besedilo
Privzeto: –
Dovoljene vrednosti: Do 32.000 znakov
top_p
Tip: Število
Privzeto: 0.95
Dovoljene vrednosti: 0 do 1
stream
Tip: Da/Ne
Privzeto: false
Dovoljene vrednosti: –
image_url
Optional image URL to analyze
Tip: Besedilo
Privzeto: –
Dovoljene vrednosti: –
max_tokens
Tip: Celo število
Privzeto: 4096
Dovoljene vrednosti: 1 do 32.000
temperature
Tip: Število
Privzeto: 1
Dovoljene vrednosti: 0 do 2
system_prompt
Optional system instruction
Tip: Besedilo
Privzeto: –
Dovoljene vrednosti: Do 8000 znakov

Oznake

google
deepmind
flagship
multimodal
deep-think
long-context
1m-context
video-understanding

Primeri uporabe

Kaj se uporablja za

Long-video and long-PDF analysis
Scientific research and literature review
Coding agents with Deep Think reasoning
Search-grounded enterprise chatbots
Multimodal data extraction at scale
Audio transcription and analysis with reasoning
Whole-codebase refactoring and migration

Vsi modeli v Multimodalno

Pogosta vprašanja

Kaj je Gemini 3.1 Pro?

Gemini 3.1 Pro je model podjetja Google DeepMind iz kategorije Multimodalno. Na Railwailu ga lahko pokličete z ključem API prek Railwailovega API-ja.

Koliko stane Gemini 3.1 Pro na Railwailu?

Na Railwail stane Gemini 3.1 Pro 2,40 $ na 1M vhodnih žetonov in 14,40 $ na 1M izhodnih žetonov. Zaračunano vam je tisto, kar vsaka zahteva dejansko porabi. Uporaba se plača s predplačanimi krediti; 1 kredit je enak 0,01 $.

Kako veliko je kontekstno okno Gemini 3.1 Pro?

Kontekstno okno Gemini 3.1 Pro vsebuje 1.048.576 žetonov. Odgovor je lahko dolg do 65.536 žetonov.

Kako hiter je Gemini 3.1 Pro?

Za Gemini 3.1 Pro je na Railwailu še premalo izmerjenih zagonov, da bi navedli čas izvajanja. Odvisno je od vnosa, nastavitev in obremenitve pri ponudniku.

Je Gemini 3.1 Pro boljši od BLIP?

To je odvisno od naloge. Gemini 3.1 Pro (Google DeepMind) in BLIP (Salesforce) sta oba modela iz kategorije Multimodalno. Stran za primerjavo prikazuje njune cene in specifikacije drug ob drugem.

Primerjaj Gemini 3.1 Pro in BLIP

Ali Gemini 3.1 Pro lahko obdeluje slike?

Da. Gemini 3.1 Pro sprejema slike kot vhod poleg besedila.

Kako uporabljam Gemini 3.1 Pro prek API-ja?

Ustvarite ključ Railwailovega API-ja in pošljite zahtevo z ID-jem modela gemini-3-1-pro. Primeri kode za curl, Python in JavaScript so v razdelku API na tej strani.

Primerljivi modeli

Vsi v tej kategoriji

Claude Opus 4.7Anthropic
Anthropic's April 2026 flagship. 87.6% on SWE-bench Verified, 3x higher image resolution, output self-verification, vision + reasoning.
6,00 $/1M vhod
150 % dražje na enoto
Primerjaj Gemini 3.1 Pro in Claude Opus 4.7
Claude Sonnet 4.6Anthropic
Anthropic's balanced mid-tier model from February 2026. Best price/performance for production workloads: 5x cheaper than Opus, near-flagship quality.
3,60 $/1M vhod
50 % dražje na enoto
Primerjaj Gemini 3.1 Pro in Claude Sonnet 4.6
Gemini 3 FlashGoogle DeepMind
Google's April 2026 fast multimodal model. Combines Gemini 3 Pro's reasoning with Flash-tier latency and price. Default model in the Gemini app.
0,60 $/1M vhod
75 % cenejše na enoto
Primerjaj Gemini 3.1 Pro in Gemini 3 Flash

Uporabite Gemini 3.1 Pro prek API

En API ključ za vsak model na Railwail. Uporaba se obračuna iz vnaprej plačanih kreditov, 1 kredit = 0,01 $.

Pridobite API ključ Oglejte si vse modele