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Note: The list of supported base models is listed on the same page. If you need a base model that is not listed, please contact us at feedback@deepinfra.com
Rate limit will apply on combined traffic of all LoRA adapter models with the same base model. For example, if you have 2 LoRA adapter models with the same base model, and have rate limit of 200. Those 2 LoRA adapter models combined will have rate limit of 200.
Pricing is 50% higher than base model.
LoRA adapter model speed is lower than base model, because there is additional compute and memory overhead to apply the LoRA adapter. From our benchmarks, the LoRA adapter model speed is about 50-60% slower than base model.
You could merge the LoRA adapter with the base model to reduce the overhead. And use custom deployment, the speed will be close to the base model.
The easiest way to build AI applications with Llama 2 LLMs.The long awaited Llama 2 models are finally here!
We are excited to show you how to use them with DeepInfra. These collection of models represent
the state of the art in open source language models.
They are made available by Meta AI and the l...
Fork of Text Generation Inference.The text generation inference open source project by huggingface looked like a promising
framework for serving large language models (LLM). However, huggingface announced that they
will change the license of code with version v1.0.0. While the previous license Apache 2.0
was permissive, the new on...
Langchain improvements: async and streamingStarting from langchain
v0.0.322 you
can make efficient async generation and streaming tokens with deepinfra.
Async generation
The deepinfra wrapper now supports native async calls, so you can expect more
performance (no more t...© 2026 DeepInfra. All rights reserved.