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Zephyr ORPO 141B on DeepInfra

Zephyr · Hugging Face H4

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Last refreshed 2026-04-24. Next refresh: weekly.

Why use Zephyr ORPO 141B on DeepInfra?

DeepInfra offers Zephyr ORPO 141B with pay-as-you-go pricing at $0.65/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.

Input / 1M
$0.65
Output / 1M
$0.65
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export DEEPINFRA_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
Model ID
zephyr-orpo-141b

Request 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="zephyr-orpo-141b",
    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.

Pricing

TypePrice (per 1M)
Input tokens$0.65
Output tokens$0.65

Capabilities

Structured Outputs

About Zephyr ORPO 141B

The Zephyr ORPO 141B is a cutting-edge large language model by Hugging Face, developed in partnership with Argilla and KAIST. It employs a Mixture of Experts (MoE) architecture, consisting of 141 billion parameters, with 39 billion active during operation. The model is derived from the Mixtral-8x22B framework and fine-tuned using the innovative Odds Ratio Preference Optimization (ORPO) method, which improves computational efficiency by removing the need for a separate supervised fine-tuning phase. Zephyr ORPO demonstrates impressive proficiency in tasks such as open-ended conversations, question answering, and coding assistance, evidenced by high scores on benchmarks like MT Bench (8.17) and IFEval (65.06) 139. The model, trained on a dataset of 7,000 instances, is optimized for multi-turn dialogues, making it ideal for interactive AI applications. However, attention should be paid to its lack of alignment with human safety preferences, as this could lead to problematic outputs 4512.

FAQ

What does Zephyr ORPO 141B cost on DeepInfra?

On DeepInfra, Zephyr ORPO 141B costs $0.65 per 1M input tokens and $0.65 per 1M output tokens.

Who created Zephyr ORPO 141B?

Zephyr ORPO 141B was created by Hugging Face H4 as part of the Zephyr model family.

Is Zephyr ORPO 141B open source?

Zephyr ORPO 141B's open source status is unknown in the seed data.

Get Started

Model Specs

Released2023-10-26
Parameters141B
ArchitectureDecoder Only