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Google: Gemini 3.5 Flash (batch): AI model

Context window:
1,048,576 tokens
Input:
$0.75/1M tokens
Output:
$4.5/1M tokens
Type:
text, image, video, audio
  • Vision
  • Tools
  • Streaming
  • Long context

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

Google: Gemini 3.5 Flash (batch) is a AI model from Google, available through Hormouz via 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:batch",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Specs

VendorGoogle
TypeText, Image, Video, Audio
Context window1,048,576 tokens
Pricing$0.75/M in · $4.50/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

Design Arena

How Design Arena works ↗

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:batch",
    "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:batch",
    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:batch",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

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Updated 2026-10-13