Using Phi-3 Medium 4K on DeepInfra
Implementation guide · Phi-3 · Microsoft Research
DeepInfra exposes Phi-3 Medium 4K through model ID phi-3-medium-4k. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
- 1
- 2Use the DeepInfra SDK or REST API to call
phi-3-medium-4k— see the documentation for request format. - 3
Code Examples
pip install openaiDEEPINFRA_API_KEYphi-3-medium-4kDeepInfra 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.
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="phi-3-medium-4k",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on DeepInfra
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.14 |
| Output tokens | $0.41 |
Capabilities
About Phi-3 Medium 4K
The Phi-3 Medium 4K, developed by Microsoft, is a state-of-the-art large language model with 14 billion parameters. It is engineered for efficiency across various tasks, particularly excelling in reasoning capabilities. This model is designed to handle 4,096 token context lengths, allowing for the processing of longer input sequences. Leveraging a dense, decoder-only Transformer architecture, it incorporates techniques like supervised fine-tuning and direct preference optimization to align with human preferences and safety standards. The model supports multilingual data, although it is primarily trained in English.