Pricing
- Input Tokens: $0.088 /M tokens
- Output Tokens: $0.385 /M tokens
- Cache Read: $0.011 /M tokens
Input Modalities
Output Modalities
- Text
Context length
- 262K tokens
Max output
- 131K tokens
Try this model
Python
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AIHUBMIX_API_KEY"],
base_url="https://aihubmix.com/v1",
)
response = client.chat.completions.create(
model="deepinfra-gemma-4-26b-a4b-it",
messages=[
{
"role": "user",
"content": "Hello, how are you?"
}
],
max_tokens=1024,
stream=False,
)
print(response.choices[0].message.content)Gemini 4 Argon is Google DeepMind’s multimodal reasoning model for complex software engineering, financial research, legal drafting, and cybersecurity defense. It supports sustained reasoning across long, multi-step workflows, combining coding capabilities with chart and long-video understanding. It can also autonomously discover, validate, and patch software vulnerabilities.
Input price: $1.5/M, Text output: $7.5/M, Image output: $30/M
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Gemini 3.8 Flash-Lite TTS (gemini-3.8-flash-lite-tts) is Google's fast, cost-efficient workhorse text-to-speech model, built to replace gemini-3.1-flash-tts-preview for high-throughput production workloads.
Gemini 3.8 Flash TTS (gemini-3.8-flash-tts) is Google's 3.8 Flash text-to-speech audio model, designed to deliver studio-grade sound fidelity, expressive performance, and long-form stability.
Gemini 3.8 Flash is Google's most intelligent Flash-series model, designed for long-running software engineering tasks, autonomous agents, and complex enterprise workflows, while retaining the Flash series' fast responsiveness and cost-effectiveness.
(This model has been officially taken offline; requests to gemini-3.5-flash will now be automatically routed to gemini-3.8-flash.)Gemini 3.7 Flash is Google’s natively multimodal reasoning model for coding, agents, web development, and knowledge work. It supports a 1M-token context window and adjustable thinking levels. Compared with Gemini 3.6 Flash, it improves coding, tool use, multi-step planning, and instruction following.