Using Gemma 7B Instruct on Replicate API
Implementation guide · Gemma · Google DeepMind
Replicate API exposes Gemma 7B Instruct through model ID google-deepmind/gemma-7b-it. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-04-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the Replicate API SDK or REST API to call
google-deepmind/gemma-7b-it— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENgoogle-deepmind/gemma-7b-itReplicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
import replicate
# reads REPLICATE_API_TOKEN from env
# google-deepmind/gemma-7b-it format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"google-deepmind/gemma-7b-it",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Pricing on Replicate API
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.25 |
Capabilities
About Gemma 7B Instruct
Gemma 7B Instruct is a cutting-edge large language model developed by Google DeepMind, boasting 7 billion parameters. As part of the Gemma family, it benefits from the advanced research underpinning Google's Gemini models. This model is optimized for text generation tasks, excelling in areas like question answering and summarization, and it is finely tuned to follow instructions effectively. Despite its compact size, Gemma 7B Instruct performs impressively on benchmarks, making it versatile for deployment across various hardware platforms, from laptops to cloud infrastructure.