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Kan bruges 24 timer efter tilmelding, op til 5 kørsler pr. dag og højst 2 credits pr. kørsel. Andre login-metoder starter uden credits. Nok til 27 kørsler af denne model.
02
Om Gemini 3 Flash
Kort sagtFra 23. september 2026
Gemini 3 Flash er en model af Google DeepMind i kategorien Multimodal. På Railwail koster Gemini 3 Flash 0,60 US$ pr. 1M inputtokens og 3,60 US$ pr. 1M outputtokens. Kontekstvinduet indeholder 1.048.576 tokens, og et svar kan være op til 65.536 tokens langt.
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.
Baggrund
Om Google DeepMind
Grundlagt 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.
Parametre
Undisclosed (sparse MoE, smaller and sparser than Gemini 3.1 Pro)
Kontekst
1.048.576 tokens
Funktioner
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.
Licens: 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.
Sikkerhedstests: Evaluated under Google DeepMind's Frontier Safety Framework v2 with internal red teams and external evaluators.
Kendte begrænsninger
Below Gemini 3.1 Pro on the hardest reasoning and long-context benchmarks
curl https://railwail.com/api/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3-flash",
"messages": [
{
"role": "user",
"content": "Explain what a vector database is in two sentences."
}
],
"max_tokens": 1024
}'
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/api/v1",
)
completion = client.chat.completions.create(
model="gemini-3-flash",
messages=[
{
"role": "user",
"content": "Explain what a vector database is in two sentences.",
},
],
max_tokens=1024,
)
print(completion.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/api/v1",
});
const completion = await client.chat.completions.create({
model: "gemini-3-flash",
messages: [
{
role: "user",
content: "Explain what a vector database is in two sentences."
}
],
max_tokens: 1024
});
console.log(completion.choices[0].message.content);
// npm install railwail
import railwail from "railwail";
const rw = railwail(process.env.RAILWAIL_API_KEY);
const res = await rw.chat("gemini-3-flash", [
{ role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });
console.log(res.choices[0].message.content);
Gemini 3 Flash er en model fra Google DeepMind i kategorien Multimodal. På Railwail kan du kalde den med en API-nøgle via Railwail API.
Hvad koster Gemini 3 Flash på Railwail?
På Railwail koster Gemini 3 Flash 0,60 US$ pr. 1M inputtokens og 3,60 US$ pr. 1M outputtokens. Du betaler for det, som hver anmodning faktisk bruger. Forbrug betales fra forudbetalte credits; 1 credit svarer til 0,01 US$.
Hvad er kontekstvinduet for Gemini 3 Flash?
Kontekstvinduet for Gemini 3 Flash indeholder 1.048.576 tokens. Et svar kan være op til 65.536 tokens langt.
Hvor hurtig er Gemini 3 Flash?
Der er endnu ikke nok målte kørsler af Gemini 3 Flash på Railwail til at angive en udførelsestid. Det afhænger af inputtet, indstillingerne og belastningen hos provideren.
Er Gemini 3 Flash bedre end BLIP?
Det afhænger af opgaven. Gemini 3 Flash (Google DeepMind) og BLIP (Salesforce) er begge modeller i kategorien Multimodal. Sammenligningssiden viser deres priser og specifikationer side om side.
Ja. Gemini 3 Flash accepterer billeder som input ud over tekst.
Hvordan bruger jeg Gemini 3 Flash via API'en?
Opret en Railwail API-nøgle og send din anmodning med model-ID'en gemini-3-flash. Kodeeksempler til curl, Python og JavaScript findes i API-sektionen på denne side.
