DeepInfra raises $107M Series B to scale the inference cloud — read the announcement
At DeepInfra we host the best open source LLM models. We are always working hard to make our APIs simple and easy to use.
Today we are excited to announce a very easy way to quickly try our models like Llama2 70b and Mistral 7b and compare them to OpenAI's models. You only need to change the API endpoint URL and the model name to quickly see if these models are a good fit for your application.
Here is a quick example of how to use the OpenAI Python client with our models:
import openai
# Point OpenAI client to our endpoint
openai.api_base = "https://api.deepinfra.com/v1/openai"
# Just leave the API key empty. You don't need it to try our models.
openai.api_key = ""
# Your chosen model here
MODEL_DI = "meta-llama/Llama-2-70b-chat-hf"
chat_completion = openai.ChatCompletion.create(
model="meta-llama/Llama-2-70b-chat-hf",
messages=[{"role": "user", "content": "Hello world"}],
stream=True,
)
# print the chat completion
for event in chat_completion:
print(event.choices)
Rate limits on no API key
To make it as simple as possible you don't even have to create an account with DeepInfra to
try our models. Just pass empty string as api_key and you are good to go. We rate limit the
unauthenticated requests by IP address.
Pricing and Production ready
When you are ready to use our models in production, you can create an account at DeepInfra and get an API key. We offer the best pricing for the llama 2 70b model at just $1 per 1M tokens. If you need any help, just reach out to us on our Discord server.
Long Context models incomingMany users requested longer context models to help them summarize bigger chunks
of text or write novels with ease.
We're proud to announce our long context model selection that will grow bigger in the comming weeks.
Models
Mistral-based models have a context size of 32k, and amazon recently r...
DeepInfra Raises $107M Series B to Scale Inference InfrastructureDeepInfra has raised $107 million in Series B funding to scale its inference cloud, expand global capacity, and support the next generation of open-source and agentic AI workloads.
Reliable JSON-Only Responses with DeepInfra LLMs<p>When large language models are used inside real applications, their role changes fundamentally. Instead of chatting with users, they become infrastructure components: extracting information, transforming text, driving workflows, or powering APIs. In these scenarios, natural language is no longer the desired output. What applications need is structured data — and very often, that structure is […]</p>
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