Replicate API exposes Arctic through model ID snowflake/snowflake-arctic-instruct. 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
snowflake/snowflake-arctic-instruct— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENsnowflake/snowflake-arctic-instructReplicate 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
# snowflake/snowflake-arctic-instruct format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"snowflake/snowflake-arctic-instruct",
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 | $0.65 |
| Output tokens | $2.75 |
Capabilities
About Arctic
Snowflake Arctic is an advanced large language model tailored for enterprise applications by Snowflake AI Research. It features an innovative Dense-MoE Hybrid transformer architecture, combining a 10 billion parameter dense transformer with a 128 x 3.66 billion parameter MoE MLP, totaling 480 billion parameters but utilizing only 17 billion actively. This structure optimizes efficiency, particularly for tasks like SQL generation, coding, and instruction following. The model's training spanned a diverse dataset of 3.5 trillion tokens, focusing on enterprise needs. Despite its capabilities, Arctic's deployment presents challenges due to its size, and it remains vulnerable to inaccuracies with unclear inputs.