Last refreshed 2026-06-15. 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.
Setup recipe
Python + curlpip install openaiexport DEEPINFRA_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],gemma-1.1-7bRequest 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
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.15 |
Capabilities
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.