Billed by the tokens actually used; the unused part of the reservation is refunded.
New here?
10 free credits (US$0.10) when you sign up with Google
Usable 24 hours after sign-up, up to 5 runs per day and at most 2 credits per run. Other sign-in methods start without credits. Enough for 27 runs of this model.
02
About Gemini 3 Flash
TL;DRAs of 23 September 2026
Gemini 3 Flash is a model by Google DeepMind in the Multimodal category. On Railwail, Gemini 3 Flash costs US$0.60 per 1M input tokens and US$3.60 per 1M output tokens. The context window holds 1,048,576 tokens, and one response can be up to 65,536 tokens long.
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.
Background
About Google DeepMind
Founded 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.
Parameters
Undisclosed (sparse MoE, smaller and sparser than Gemini 3.1 Pro)
Context
1,048,576 tokens
Capabilities
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.
License: 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.
Safety testing: Evaluated under Google DeepMind's Frontier Safety Framework v2 with internal red teams and external evaluators.
Known limitations
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 is a model by Google DeepMind in the Multimodal category. On Railwail you can call it with an API key through the Railwail API.
How much does Gemini 3 Flash cost on Railwail?
On Railwail, Gemini 3 Flash costs US$0.60 per 1M input tokens and US$3.60 per 1M output tokens. You are charged for what each request actually uses. Usage is paid from prepaid credits; 1 credit equals US$0.01.
What is the context window of Gemini 3 Flash?
The context window of Gemini 3 Flash holds 1,048,576 tokens. One response can be up to 65,536 tokens long.
How fast is Gemini 3 Flash?
There are not enough measured runs of Gemini 3 Flash on Railwail yet to state a run time. It depends on the input, the settings and the load at the provider.
Is Gemini 3 Flash better than BLIP?
That depends on the task. Gemini 3 Flash (Google DeepMind) and BLIP (Salesforce) are both models in the Multimodal category. The comparison page shows their prices and specifications side by side.
Yes. Gemini 3 Flash accepts images as input in addition to text.
How do I use Gemini 3 Flash through the API?
Create a Railwail API key and send your request with the model ID gemini-3-flash. Code examples for curl, Python and JavaScript are in the API section of this page.
