Using Fireworks Zephyr-7B-beta on Fireworks AI

Implementation guide · Zephyr · Hugging Face H4

ServerlessOpen Source

Fireworks AI exposes Fireworks Zephyr-7B-beta through model ID fireworks-zephyr-7b-beta. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-05-19. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Fireworks AI and generate an API key.
  2. 2
    Use the Fireworks AI SDK or REST API to call fireworks-zephyr-7b-beta — see the documentation for request format.
  3. 3
    You'll be billed $0.10/1M input, $0.10/1M output tokens. See full pricing.
API PortalDocumentationPricing

Code Examples

Install
pip install openai
API key
FIREWORKS_API_KEY
Model ID
fireworks-zephyr-7b-beta

Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["FIREWORKS_API_KEY"],
    base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
    model="fireworks-zephyr-7b-beta",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Fireworks AI

TypePrice (per 1M)
Input tokens$0.10
Output tokens$0.10

Capabilities

No model capability flags are currently sourced.

About Fireworks Zephyr-7B-beta

Fireworks Zephyr-7B-beta is Hugging Face H4's Zephyr model. It offers an 8K-token context window with weights openly available for self-hosting.

Full model details →

Model Specs

Released2023-10-26
Parameters7B
Context8k
ArchitectureDecoder Only

More Models on Fireworks AI

Zephyr 7B Beta
All models on Fireworks AI →

Provider

Fireworks AI

San Mateo, California, United States