Gemma 4 26B A4B It
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Gemma 4 26B A4B It

gemma-4-26b-a4b-itllms.txt
Google
A Mixture-of-Experts model that activates only 4B parameters per inference,delivering high-performance reasoning with a fraction of the memory cost - idealfor cost-efficient, high-throughput server deployments.

Pricing

  • Input Tokens: $0.140 /M tokens
  • Output Tokens: $0.400 /M tokens
  • Cache Read: $0.000 /M tokens

Input Modalities

    Output Modalities

    • Text

    Providers

    Google AI Studio google-gemma-4-26b-a4b-it
    Pricing$0.140$0.400
    Cache$0.000
    Context262K
    Max output131K
    Latency0.8S
    Throughput19.7TPS
    Uptime
    100.00% uptime 2 days ago
    100.00% uptime yesterday
    100.00% uptime today
    Deepinfra deepinfra-gemma-4-26b-a4b-it
    Pricing$0.088$0.385
    Cache$0.011
    Context128K
    Max output128K
    Latency0.5S
    Throughput21.3TPS
    Uptime
    100.00% uptime 2 days ago
    100.00% uptime yesterday
    100.00% uptime today

    Performance for gemma-4-26b-a4b-it

    Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).

    Uptime
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    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="gemma-4-26b-a4b-it",
        messages=[
          {
            "role": "user",
            "content": "Hello, how are you?"
          }
        ],
        max_tokens=1024,
        stream=False,
    )
    
    print(response.choices[0].message.content)

    Frequently asked questions

    What is Gemma 4 26B A4B It?

    A Mixture-of-Experts model that activates only 4B parameters per inference,delivering high-performance reasoning with a fraction of the memory cost - idealfor cost-efficient, high-throughput server deployments.