We use essential cookies to make our site work. With your consent, we may also use non-essential cookies to improve user experience and analyze website traffic…

Nemotron 3 Nano Omni — the first multimodal model in the Nemotron 3 family, now on DeepInfra!

Compare Llama2 vs OpenAI models for FREE.
Published on 2023.09.28 by Nikola Borisov
Compare Llama2 vs OpenAI models for FREE.

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)
copy

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.

Related articles
Introducing GPU Instances: On-Demand GPU Compute for AI WorkloadsIntroducing GPU Instances: On-Demand GPU Compute for AI WorkloadsLaunch dedicated GPU containers in minutes with our new GPU Instances feature, designed for machine learning training, inference, and compute-intensive workloads.
LLM API Provider Performance KPIs 101: TTFT, Throughput & End-to-End GoalsLLM API Provider Performance KPIs 101: TTFT, Throughput & End-to-End Goals<p>Fast, predictable responses turn a clever demo into a dependable product. If you’re building on an LLM API provider like DeepInfra, three performance ideas will carry you surprisingly far: time-to-first-token (TTFT), throughput, and an explicit end-to-end (E2E) goal that blends speed, reliability, and cost into something users actually feel. This beginner-friendly guide explains each KPI [&hellip;]</p>
How to deploy google/flan-ul2 - simple. (open source ChatGPT alternative)How to deploy google/flan-ul2 - simple. (open source ChatGPT alternative)Flan-UL2 is probably the best open source model available right now for chatbots. In this post we will show you how to get started with it very easily. Flan-UL2 is large - 20B parameters. It is fine tuned version of the UL2 model using Flan dataset. Because this is quite a large model it is not eas...