Last refreshed 2026-06-15. 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 + curlInstall
pip install openaiAuth
export DEEPINFRA_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],Model ID
zephyr-orpo-141bRequest 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
| Type | Price (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.
Model Specs
Released2023-10-26
Parameters141B
ArchitectureDecoder Only
Knowledge cutoff2024-01