Gemini 4 Carbon | Google LLM API Pricing & Performance

Name: Gemini 4 Carbon API
Brand: google
Price: 4 USD
Availability: InStock

google/gemini-4-carbon

Veröffentlichungsdatum: 2026-11-11

1,048,576 context · $4.00/M input tokens · $20.00/M output tokens

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode...

Preise

Pay-per-Use

Keine Vorabkosten, zahlen Sie nur, was Sie nutzen

Eingabe$4.00 / M Tokens

Ausgabe$20.00 / M Tokens

Cache Read$0.20 / M Tokens

Cache Write$0.38 / M Tokens

Modell ausprobieren

google/gemini-4-carbon

Online

Hallo! Ich bin ein hilfreicher KI-Assistent. Womit kann ich helfen?

Bereit, dieses Modell in einem lokalen Coding-Agent zu verwenden?Agent-Setup

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: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'google/gemini-4-carbon',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  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: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'google/gemini-4-carbon',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Modelleinführung

Google: Gemini 4 Carbon

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode...

This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.

Why It Looks Great

text+image+file+audio+video->text architecture for Audio, file, Image, Text, Video to Text workloads
1048576 context window for long prompts, document analysis, and multi-turn workflows
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
Reasoning controls available through supported parameters

Key Features

Context Window: 1048576 tokens
Max Input: 1048576 tokens
Max Output: 943718 tokens
Vision: Supported
Function Calling: Supported
Structured Outputs: Supported
Image Generation: Not listed
Audio Input: Supported
Supported Parameters: include_reasoning, max_tokens, reasoning, reasoning_effort, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p

Specifications

Specification	Value
Provider	google
Model Type	Chat Completions model
Architecture	text+image+file+audio+video->text
Context Window	1048576 tokens
Max Input	1048576 tokens
Max Output	943718 tokens
Input	Audio, file, Image, Text, Video
Output	Text
Vision	Supported
Function Calling	Supported
Structured Outputs	Supported
Release Date	November 11, 2026

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-4-carbon

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-4-carbon",
    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-4-carbon",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: google/gemini-4-carbon
Provider: google

Info

Anbietergoogle

Typllm

Unterstützte Funktionen

Eingabe

TextBildAudio

Ausgabe

Text

Kontext1,048,576

Max. Ausgabe943,718

Vision✓ Unterstützt

Function Calling✓ Unterstützt

API-Zugriffsanleitung

Base URLhttps://llm.wavespeed.ai/v1

API-Endpunktchat/completions

Modell-IDgoogle/gemini-4-carbon

Häufige Fragen zu Gemini 4 Carbon

Wie viel kostet die Gemini 4 Carbon-API?+

Preise auf WaveSpeedAI: $4.00 pro Million Input-Tokens und $20.00 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 4 Carbon?+

Gemini 4 Carbon unterstützt bis zu 1049K Kontext-Tokens und bis zu 944K Output-Tokens pro Anfrage.

Ist Gemini 4 Carbon OpenAI-kompatibel?+

WaveSpeedAI stellt Gemini 4 Carbon 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 4 Carbon?+

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.