Last refreshed 2026-06-15. Next refresh: weekly.
Why use airoboros L2 70B 2.2.1 on DeepInfra?
DeepInfra offers airoboros L2 70B 2.2.1 with pay-as-you-go pricing at $0.45/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.
Setup recipe
Python + curlpip install openaiexport DEEPINFRA_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],airoboros-l2-70b-2.2.1Request 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="airoboros-l2-70b-2.2.1",
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 | $0.45 |
| Output tokens | $0.65 |
Capabilities
About airoboros L2 70B 2.2.1
The Airoboros L2 70B 2.2.1, built on the Llama 2 architecture, is a large language model optimized for instruction following rather than casual conversation. With 70 billion parameters, it excels in tasks like instruction following, question answering, summarization, and coding. The model employs a unique prompting format, A chat.\nUSER: {prompt}\nASSISTANT:, and benefits from using explicit delimiters to reduce hallucinations in closed-context instructions. A limitation is that Q4_0 quantization yields unusable outputs.