Intelligence
Index v5.0
Custom pricing for production workloads
Gemini 3.8 Flash is Google’s most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents and complex enterprise workflows, at Flash speed and cost efficiency.
Gemini 3.8 Flash is Google's most intelligent Flash model, built for long-horizon software engineering, autonomous agents, and complex enterprise workflows.
google/gemini-3.8-flashhttps://api.aimlapi.com/v1Gemini 3.8 Flash, internally codenamed "Skimaki," is Google's most intelligent Flash model, released September 2, 2026, the third Flash update in about five weeks, following 3.6 Flash (July 21) and 3.7 Flash (August 13). It's engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows, at Flash speed and cost efficiency. Google also released a cybersecurity-focused sibling, Gemini 3.8 Flash Cyber, alongside it.
| Developer | |
|---|---|
| Model ID | google/gemini-3.8-flash |
| Context window | 1,048,576 tokens |
| Max output | 65,536 tokens |
| Supported inputs | Image, Text |
| Output | Text |
Strong agentic coding benchmarks
Google reports Gemini 3.8 Flash ahead of Anthropic's Opus 5 and OpenAI's GPT-5.6 Sol on several practical benchmarks, including Vals Finance Agent v2 (61.4% vs 58.6% and 53.8%), CharXiv Reasoning (86.2% vs 83.7%), and LVBench agentic mode (87.8% vs 75.4%).
Built for long-running agentic loops
Designed for multi-step orchestration, where an agent breaks a complex task into sequential actions and executes them with less human hand-holding, code generation, refactoring, and production-ready agents are the headline use cases.
Same speed and cost as 3.7 Flash
Google says the coding, agentic, and reasoning upgrades come at the same speed and low cost as the previous Flash release.
Sources: blog.google, 9to5google.com, officechai.com
Gemini 3.8 Flash is documented as suited for long-horizon software engineering, including real-world coding benchmarks and complex multi-file refactoring. It is also suited for autonomous agents, with resilient multi-step planning and tool orchestration workflows.
It is documented for complex enterprise workflows, including demanding domain tasks and large-scale data pipelines with deep reasoning and high factual rigor. Google also describes it as well-suited for general-purpose, production-ready agents and agentic knowledge workflows.
It is additionally presented for interactive app building and rich visual experiences, including design adherence, interactive components, screenshots-to-app workflows, and 3D/physics-oriented app creation.
See how Gemini 3.8 Flash compares in intelligence, generation speed, cost per task and latency. Data retrieved Nov 3, 2026.
Compare 6 models available on AI/ML API across 5 independent benchmarks.
Expert-written questions across academic subjects.
Graduate-level science questions written to resist web search.
Agentic tasks completed in a command-line environment.
Reasoning across long documents of about 100k tokens.
Python coding tasks drawn from scientific research.
| Usage | Price | Unit |
|---|---|---|
| Input | $0.75 | 1M tokens |
| Output | $3.75 | 1M tokens |
| Cached input | $0.075 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
| $0.75 | $3.75 | |
| $0.3 | $2.5 | |
| $0.75 | $3.75 | |
| $1.5 | $7.5 | |
| $2 | $10 |
Give your agent the model details, code and documentation.
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "google/gemini-3.8-flash",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "google/gemini-3.8-flash",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "google/gemini-3.8-flash",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Gemini 3.8 Flash has a 1,048,576 tokens context window and can return up to 65,536 tokens.
Gemini 3.8 Flash takes image, text as input and returns text.
Use google/gemini-3.8-flash as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Gemini 3.8 Flash became available on September 2, 2026.
Gemini 3.8 Flash costs $0.75 input and $3.75 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Yes, Gemini 3.8 Flash can stream responses as they are generated.
Yes, Gemini 3.8 Flash accepts image input alongside text.
Gemini 3.8 Flash was built by Google.