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Google: Gemini 3.5 Flash: AI model

Gemini 3.5 Flash is a Google multimodal model for reasoning, coding and everyday chat, with a 1.0M-token context window. Available via Hormouz with stable access from inside Iran.

Context window:
1,048,576 tokens
Input:
$1.5/1M tokens
Output:
$9/1M tokens
Type:
text, image, video, audio
  • Vision
  • Tools
  • Streaming
  • Long context

Thinking levels: Always thinks · high · medium · low · minimal

Gemini 3.5 Flash is a Google Gemini-family model built for reasoning, coding, mathematics and general chat. It supports configurable "thinking" (reasoning effort levels) so you can trade cost and latency for accuracy on hard tasks. It accepts text, images, video, PDFs and files and audio and returns text, with a context window of up to 1.0M tokens.

Its multimodal input makes it suitable for document understanding, chart and image analysis, and workflows that mix text with images and video. With thinking enabled it is stronger on multi-step reasoning; with thinking minimal it responds quickly and cheaply.

Pricing is usage-based at $1.5/M in · $9/M out. Gemini 3.5 Flash is served through Hormouz behind an OpenAI-compatible API, with stable access from inside Iran.

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...

Quickstart

curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.5-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Specs

VendorGoogle
TypeText, Image, Video, Audio
Context window1,048,576 tokens
Pricing$1.50/M in · $9.00/M out
APIChat Completions
CapabilitiesStreaming · Vision · Tools

Benchmarks

32.6
Intelligence Index
Better than 61% of models we compared
70.1
Coding Index
Better than 81% of models we compared
26
Agentic Index
Better than 61% of models we compared

Reasoning

GPQA Diamond
Graduate-level scientific reasoning
92.2%
HLE
Humanity's Last Exam
42.7%
IFBench
Instruction-following
76.3%
AA-LCR
Long-context reasoning
73.3%
CritPt
Research-level physics reasoning
13.1%
AA Omniscience
Broad factual knowledge accuracy
51.4%
Non-Hallucination
Rate of avoiding fabricated answers
37.8%

Coding

SciCode
Python for scientific computing
53.9%
Terminal-Bench Hard
Agentic coding & terminal use
40.9%

Agentic

τ²-Bench
Tool-use agents in dual-control scenarios
95.3%
GDPval
Economically valuable tasks
35.2%

Source: Artificial Analysis

Ranking distribution

First
66,099
Second
55,568
Third
6,867
Fourth
3,426

22531 tournaments ?

Agentic Game Dev
Top 54%
1,180Elo
Win rate: 55.4%
Agentic HTML Slides
Top 67%
1,162Elo
Win rate: 45.8%
Agentic Slides
Top 33%
1,244Elo
Win rate: 57.5%
Agentic Slides (HTML)
Top 67%
1,162Elo
Win rate: 45.7%
Agentic Slides (Python)
Top 22%
1,242Elo
Win rate: 57.8%
Android Native
Top 38%
1,199Elo
Win rate: 57.7%
Full-Stack
Top 45%
1,195Elo
Win rate: 56.2%
Godot Game Dev
Top 83%
1,098Elo
Win rate: 43%
HTML Slides
Top 83%
1,142Elo
Win rate: 46.5%Avg time: 239s
Mobile Apps
Top 52%
1,169Elo
Win rate: 51%
PPTX Slides
Top 25%
1,244Elo
Win rate: 57.7%
Python Slides
Top 37%
1,247Elo
Win rate: 57.4%Avg time: 305s
Web Apps
Top 50%
1,196Elo
Win rate: 52.6%
3D
Top 23%
1,254Elo
Win rate: 56.3%Avg time: 70.5s
ASCII Art
Top 21%
1,264Elo
Win rate: 59%Avg time: 85.2s
Code
Top 20%
1,271Elo
Win rate: 54.3%Avg time: 84.7s
Data Viz
Top 27%
1,243Elo
Win rate: 52.9%Avg time: 70.2s
Game Dev
Top 19%
1,274Elo
Win rate: 53%Avg time: 98.9s
SVG
Top 13%
1,255Elo
Win rate: 59%Avg time: 82.5s
UI Component
Top 18%
1,281Elo
Win rate: 55.1%Avg time: 68.4s
Website
Top 20%
1,272Elo
Win rate: 53.9%Avg time: 88.4s

Metrics sourced from Design Arena

Code example

cURL
curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.5-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
Python
from openai import OpenAI
client = OpenAI(api_key="ng-YOUR_API_KEY", base_url="https://api.hormouz.net/v1")
response = client.chat.completions.create(
    model="google/gemini-3.5-flash",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
JavaScript
import OpenAI from "openai";
const client = new OpenAI({ apiKey: "ng-YOUR_API_KEY", baseURL: "https://api.hormouz.net/v1" });
const response = await client.chat.completions.create({
  model: "google/gemini-3.5-flash",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

Buy the Google: Gemini 3.5 Flash API, paid in rial

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  • One Hormouz key reaches Google: Gemini 3.5 Flash and 600+ other models, and you pay only for what you use.
  • No VPN and no risk of a banned account; just change the base URL to api.hormouz.net/v1.
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FAQ

What inputs does Gemini 3.5 Flash accept?
It accepts text, images, video, PDFs and files and audio and returns text. Reasoning effort ("thinking") is configurable.
What is the context window of Gemini 3.5 Flash?
Up to 1.0M tokens, suitable for very long documents and large codebases.
How much does Gemini 3.5 Flash cost?
Usage-based pricing: $1.5/M in · $9/M out.
How does Gemini 3.5 Flash perform on benchmarks?
Independent scores from Artificial Analysis are shown in the Benchmarks section above, grouped by reasoning, coding and agentic tasks.
How do I access Gemini 3.5 Flash from inside Iran?
Create an account on Hormouz and generate an API key. Hormouz provides stable access from inside Iran via an OpenAI-compatible API.

Updated 2026-10-13