google/gemini-3.5-flash
Veröffentlichungsdatum: 2026-05-19
1,048,576 context · $1.50/M input tokens · $9.00/M output tokens
Gemini 3.5 Flash is Google’s high-efficiency multimodal model, delivering near-Pro-level reasoning and coding capabilities with Flash-class speed and cost efficiency. It is purpose-built for advanced coding workflows and parallel agentic execution, while supporting a wide range of input modalities including text, images, video, audio, and PDFs.
The model defaults to a medium reasoning mode to balance latency, quality, and cost, while also offering configurable thinking levels — minimal, low, medium, and high — for more precise performance and efficiency tuning across different workloads.
Preise
Pay-per-Use
Keine Vorabkosten, zahlen Sie nur, was Sie nutzen
Modell ausprobieren
API-Nutzung
Verwenden Sie die folgenden Codebeispiele zur Integration mit unserer API:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
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 ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
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 ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Modelleinführung
Google: Gemini 3.5 Flash
Gemini 3.5 Flash is Google’s high-efficiency multimodal model, delivering near-Pro-level reasoning and coding capabilities with Flash-class speed and cost efficiency. It is purpose-built for advanced coding workflows and parallel agentic execution, while supporting a wide range of input modalities including text, images, video, audio, and PDFs.
The model defaults to a medium reasoning mode to balance latency, quality, and cost, while also offering configurable thinking levels — minimal, low, medium, and high — for more precise performance and efficiency tuning across different workloads.
Why It Looks Great
- text+image+file+audio+video->text architecture for Text, Image, Video, file, Audio to Text workloads
- 1048576 context window for long prompts, document analysis, and multi-turn workflows
- Competitive pricing at $1.5/$9 per million tokens
- Vision input support for image understanding and multimodal tasks
- Function calling and tool-use support for agentic application workflows
- Structured output support for JSON responses and schema-constrained generation
Key Features
- Context Window: 1048576 tokens
- Max Input: 983040 tokens
- Max Output: 65536 tokens
- Vision: Supported
- Function Calling: Supported
- Structured Outputs: Supported
- Image Generation: Not listed
- Audio Input: Supported
- Supported Parameters: include_reasoning, max_tokens, reasoning, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p
Specifications
| Specification | Value |
|---|---|
| Provider | |
| Model Type | Chat Completions model |
| Architecture | text+image+file+audio+video->text |
| Context Window | 1048576 tokens |
| Max Input | 983040 tokens |
| Max Output | 65536 tokens |
| Input | Text, Image, Video, file, Audio |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Structured Outputs | Supported |
How to Use
- Write your prompt - describe the task, provide context, and specify the desired output format.
- Submit - the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: google/gemini-3.5-flash
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="google/gemini-3.5-flash",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "google/gemini-3.5-flash",
"messages": [{"role": "user", "content": "Hello!"}]
}'Info
Unterstützte Funktionen
API-Zugriffsanleitung
Gemini 3.5 Flash API
google/gemini-3.5-flash
Gemini 3.5 Flash is Google’s high-efficiency multimodal model, delivering near-Pro-level reasoning and coding capabilities with Flash-class speed and cost efficiency. It is purpose-built for advanced coding workflows and parallel agentic execution, while supporting a wide range of input modalities including text, images, video, audio, and PDFs. The model defaults to a medium reasoning mode to balance latency, quality, and cost, while also offering configurable thinking levels — minimal, low, medium, and high — for more precise performance and efficiency tuning across different workloads.
Eingabe
$1.5 /M
Ausgabe
$9 /M
Kontext
1049K
Max. Ausgabe
66K
Vision
Unterstützt
Tool-Nutzung
Unterstützt
Gemini 3.5 Flash auf WaveSpeedAI testen
Zugriff auf Gemini 3.5 Flash über unsere einheitliche API — OpenAI-kompatibel, keine Kaltstarts, transparente Preise.
Häufige Fragen zu Gemini 3.5 Flash
Wie viel kostet die Gemini 3.5 Flash-API?+
Preise auf WaveSpeedAI: $1.50 pro Million Input-Tokens und $9.00 pro Million Output-Tokens. Prompt-Caching und Batch-Verarbeitung werden separat berechnet und reduzieren die effektiven Kosten bei langen, sich wiederholenden Workloads.
Wie groß ist das Kontextfenster von Gemini 3.5 Flash?+
Gemini 3.5 Flash unterstützt bis zu 1049K Kontext-Tokens und bis zu 66K Output-Tokens pro Anfrage.
Ist Gemini 3.5 Flash OpenAI-kompatibel?+
WaveSpeedAI stellt Gemini 3.5 Flash unter https://llm.wavespeed.ai/v1 über die OpenAI-kompatible Chat-Completions-Schnittstelle bereit. Bei den meisten OpenAI-SDK-Clients reichen Base-URL und API-Schlüssel; optionale Felder hängen vom Modell ab.
Wie starte ich mit Gemini 3.5 Flash?+
Melden Sie sich bei WaveSpeedAI an, erstellen Sie unter Access Keys einen API-Schlüssel und senden Sie eine Anfrage mit der oben gezeigten Modell-ID an https://llm.wavespeed.ai/v1/chat/completions. Verfügbarkeit, Fähigkeiten und Preise finden Sie im aktuellen Modellkatalog.