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Gemma 1.1 7B Instruct on DeepInfra

Gemma · Google DeepMind

ServerlessOpen Source

Last refreshed 2026-04-24. Next refresh: weekly.

Why use Gemma 1.1 7B Instruct on DeepInfra?

DeepInfra offers Gemma 1.1 7B Instruct with pay-as-you-go pricing at $0.05/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.

Input / 1M
$0.050
Output / 1M
$0.15
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export DEEPINFRA_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
Model ID
gemma-1.1-7b

Request example

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
    base_url="https://api.deepinfra.com/v1/openai"
)
response = client.chat.completions.create(
    model="gemma-1.1-7b",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Gotchas

  • DeepInfra uses "organization/model-name" format, e.g. "meta-llama/Meta-Llama-3-8B-Instruct" or "mistralai/Mistral-7B-Instruct-v0.3". See the DeepInfra model catalog for exact IDs.
  • The examples expect DEEPINFRA_API_KEY; rename it only if your application config maps the new variable.

Pricing

TypePrice (per 1M)
Input tokens$0.05
Output tokens$0.15

Capabilities

Structured Outputs

About Gemma 1.1 7B Instruct

The Gemma 1.1 7B Instruct model is a cutting-edge, lightweight large language model developed by Google. As a part of the Gemma model family, it benefits from the same foundational research and technological advancements as Google's Gemini models. Unique to this model is its instruction-tuned training, which allows it to follow directives with greater precision than its base variants. Despite its compact size of 7 billion parameters, making it suitable for deployment on resource-constrained devices like desktops, it excels in diverse tasks including question answering, summarization, logical reasoning, and coding assistance. The model employs a transformer-based, decoder-only architecture, trained on an extensive dataset with an innovative use of Reinforcement Learning from Human Feedback (RLHF) to enhance its quality, factuality, and conversational capabilities. It supports multiple precision levels and is openly available, promoting collaboration in the AI community. Nonetheless, it shares common LLM limitations like potential data biases and factual inaccuracies, which are addressed through guidelines for responsible use.

FAQ

What does Gemma 1.1 7B Instruct cost on DeepInfra?

On DeepInfra, Gemma 1.1 7B Instruct costs $0.05 per 1M input tokens and $0.15 per 1M output tokens.

What is the context window for Gemma 1.1 7B Instruct on DeepInfra?

Gemma 1.1 7B Instruct supports a 8,000 token context window on DeepInfra.

Who created Gemma 1.1 7B Instruct?

Gemma 1.1 7B Instruct was created by Google DeepMind as part of the Gemma model family.

Is Gemma 1.1 7B Instruct open source?

Gemma 1.1 7B Instruct is open source according to the seed data.

Get Started

Model Specs

Released2024-02-21
Parameters7B
Context8K
ArchitectureDecoder Only
Knowledge cutoff2023-04