LLM Reference
Featherless

Using Phi-4 14B on Featherless

Implementation guide · Phi-4 · Microsoft Research

ServerlessOpen Source

Featherless exposes Phi-4 14B through model ID microsoft/phi-4. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-09-24. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Featherless and generate an API key.
  2. 2
    Use the Featherless SDK or REST API to call microsoft/phi-4 — see the documentation for request format.
  3. 3
    You'll be billed $0.07/1M input, $0.14/1M output tokens. See full pricing.
API PortalDocumentationPricingModel Card

Code Examples

Install
pip install openai
API key
FEATHERLESS_API_KEY
Model ID
microsoft/phi-4

Use exact Featherless catalog id in modelProvider.providerModelId (HF-style org/name). Not interchangeable with LLM Reference slugs.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.featherless.ai/v1",
    api_key=os.environ["FEATHERLESS_API_KEY"],
)
response = client.chat.completions.create(
    model="microsoft/phi-4",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Pricing on Featherless

TypePrice (per 1M)
Input tokens$0.07
Output tokens$0.14

Capabilities

Structured Outputs

About Phi-4 14B

Phi-4 14B is Microsoft Research's Phi-4 model. Weights are openly available for self-hosting and scores 56.1 on GPQA.

Full model details →

Model Specs

Released2024-12-13
Parameters14B
Context16k
ArchitectureDecoder Only
Knowledge cutoff2024-06

Also available on(3)

OpenRouter$0.07/1MFireworks AI$0.90/1MMicrosoft Foundry
Compare all providers →

Provider

Featherless
Featherless