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02
O Gemini 3 Flash
UkratkoStanje: 23. septembar 2026.
Gemini 3 Flash je model od Google DeepMind iz kategorije Multimodalni. Na Railwailu, Gemini 3 Flash košta 0,60 US$ po 1M ulaznih tokena i 3,60 US$ po 1M izlaznih tokena. Kontekstni prozor sadrži 1.048.576 tokena, a jedan odgovor može biti dugačak do 65.536 tokena.
Announced April 22, 2026, Gemini 3 Flash brings Pro-grade reasoning to the Flash latency tier. 1M-token context, fully multimodal (text, image, audio, video), 65K max output. The default model in the Gemini app and AI Mode in Search. PhD-level reasoning on common benchmarks at a fraction of the cost of 3.1 Pro. Recommended for high-throughput agentic workflows, real-time multimodal chat, RAG and consumer applications.
Pozadina
O Google DeepMind
Osnovano 2010 · Mountain View, USA / London, UK
Google DeepMind is the merged AI research organisation formed in April 2023 by combining Google Brain with DeepMind. Demis Hassabis leads the unit as CEO. Flash variants have been Google's high-throughput tier since Gemini 1.5 Flash (May 2024), with Gemini 2.0 Flash (December 2024), 2.5 Flash (mid-2025) and Gemini 3 Flash (April 2026) representing the progression. DeepMind's seminal papers include 'Attention Is All You Need' (2017), AlphaGo (2016), AlphaFold (2018-2021, Nobel Prize 2024) and the Gemini Technical Report.
Gemini 3 Flash was announced April 22, 2026 as the default Flash-tier model and the new default model in the Gemini app and AI Mode in Search. It is a natively multimodal Sparse MoE Transformer engineered to combine Gemini 3 Pro's reasoning quality with Flash-grade latency, efficiency and cost. Pretraining used Google's TPU v6e infrastructure on a multi-trillion-token mixture of web text, code, books, image-text pairs, audio and video frames. Post-training combined supervised fine-tuning, RLHF, RL against verifiable rewards and distillation from larger Gemini 3.1 Pro teacher models. The architecture preserves Gemini's native multimodality across text, image, audio and video, the full tool-use API and Search grounding, while running at a fraction of Pro pricing. Gemini 3 Flash is the recommended default for high-throughput agentic workflows and consumer-facing multimodal chat.
Parametri
Undisclosed (sparse MoE, smaller and sparser than Gemini 3.1 Pro)
Kontekst
1.048.576 tokena
Mogućnosti
Pro-grade reasoning at Flash latency
1,048,576 token context window
Natively multimodal: text, image, audio and video
Search grounding and Code Execution built into the API
Function calling, JSON schema and parallel tool calls
Default model in the Gemini app and AI Mode in Search
PhD-level reasoning on common benchmarks
Available via Vertex AI, AI Studio, Gemini Enterprise, Antigravity and the Gemini app
Pretrained on a multi-trillion-token mixture of web text, code, books, scientific papers, image-text pairs, audio and video frames. Heavily distilled from larger Gemini 3.1 Pro teacher models. Post-training uses supervised fine-tuning, RLHF and RL against verifiable rewards. Knowledge cutoff in late 2025.
Licenca: Proprietary commercial license via Google AI Studio, Vertex AI and the Gemini app. Free tier available in the Gemini app and AI Mode in Search.
Testiranje sigurnosti: Evaluated under Google DeepMind's Frontier Safety Framework v2 with internal red teams and external evaluators.
Poznata ograničenja
Below Gemini 3.1 Pro on the hardest reasoning and long-context benchmarks
curl https://railwail.com/api/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3-flash",
"messages": [
{
"role": "user",
"content": "Explain what a vector database is in two sentences."
}
],
"max_tokens": 1024
}'
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/api/v1",
)
completion = client.chat.completions.create(
model="gemini-3-flash",
messages=[
{
"role": "user",
"content": "Explain what a vector database is in two sentences.",
},
],
max_tokens=1024,
)
print(completion.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/api/v1",
});
const completion = await client.chat.completions.create({
model: "gemini-3-flash",
messages: [
{
role: "user",
content: "Explain what a vector database is in two sentences."
}
],
max_tokens: 1024
});
console.log(completion.choices[0].message.content);
// npm install railwail
import railwail from "railwail";
const rw = railwail(process.env.RAILWAIL_API_KEY);
const res = await rw.chat("gemini-3-flash", [
{ role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });
console.log(res.choices[0].message.content);
Gemini 3 Flash je model od Google DeepMind iz kategorije Multimodalni. Na Railwailu ga možete pozvati s API ključem kroz Railwail API.
Koliko stoji Gemini 3 Flash na Railwailu?
Na Railwailu, Gemini 3 Flash košta 0,60 US$ po 1M ulaznih tokena i 3,60 US$ po 1M izlaznih tokena. Naplaćuje se ono što svaki zahtjev zapravo koristi. Korištenje se plaća iz unaprijed kupljenih kredita; 1 kredit jednaka je 0,01 US$.
Koliki je kontekstni prozor od Gemini 3 Flash?
Kontekstni prozor od Gemini 3 Flash sadrži 1.048.576 tokena. Jedan odgovor može biti dugačak do 65.536 tokena.
Koliko je brz Gemini 3 Flash?
Za Gemini 3 Flash na Railwailu još nema dovoljno izmjerenih pokretanja da bi se navedlo vrijeme izvršavanja. Ovisi o unošenju, postavkama i opterećenju kod pružatelja.
Je li Gemini 3 Flash bolji od BLIP?
To ovisi o zadatku. Gemini 3 Flash (Google DeepMind) i BLIP (Salesforce) su oba modela iz kategorije Multimodalni. Stranica za usporedbu prikazuje njihove cijene i specifikacije usporedno.
Da. Gemini 3 Flash prihvaća slike kao unos osim teksta.
Kako koristim Gemini 3 Flash kroz API?
Kreiraj Railwail API ključ i pošalji svoj zahtjev s ID-om modela gemini-3-flash. Primjeri koda za curl, Python i JavaScript nalaze se u odjeljku API na ovoj stranici.
