Last refreshed 2026-06-15. Next refresh: weekly.
Why use Phi-3 Medium 4K on DeepInfra?
DeepInfra offers Phi-3 Medium 4K with pay-as-you-go pricing at $0.14/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.
Compare Phi-3 Medium 4K across 3 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport DEEPINFRA_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],phi-3-medium-4kRequest 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="phi-3-medium-4k",
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.
Compare Phi-3 Medium 4K Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Microsoft Foundry | $0.45 | $1.35 |
| NVIDIA NIM | — | — |
| DeepInfra | $0.14 | $0.41 |
Pricing
| 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.