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)
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.
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.
Multi-Turn RL: A Guide to Getting Reinforcement Learning Right<p>The first multi-turn RL run you launch will spend most of its life doing something you would not call training. You watch GPU utilization sit under half, watch a step take eleven minutes, and go hunting for a bug in your gradient accumulation. There is no bug. The trainer is waiting on rollouts. This is […]</p>
Best AI Inference Platforms for Speed & Cost in 2026<p>Your monitoring dashboard says the API is fast and your invoice says the same thing in different units. Somewhere between the two, cost per completed request disappears. This guide compares the best AI inference platform options for speed and cost on the same footing: measured latency, measured throughput, current prices, and the math that turns […]</p>
GLM-5 API Benchmarks: Latency, Throughput & Cost<p>GLM-5 is the latest open-weights reasoning model released by Z AI (Zhipu AI) in February 2026, characterized by high “thinking token” usage. It is a Mixture of Experts (MoE) model with 744B total parameters and 40B active parameters, scaling up from GLM-4.5’s 355B parameters. The model was pre-trained on 28.5T tokens and features a 200K+ […]</p>
© 2026 DeepInfra. All rights reserved.