DeepInfra raises $107M Series B to scale the inference cloud — read the announcement

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.
Open-Source vs Closed-Source AI Models: Is the Gap Worth It?<p>The Artificial Analysis Intelligence Index sits at a ceiling of 57. Three frontier models — Claude Opus 4.7, Gemini 3.1 Pro Preview, and GPT-5.5 — all land in that band. Meanwhile, four open-weight models released between February and April 2026 now score 50 or above on the same index. A year ago, the best open-weight […]</p>
Guaranteed JSON output on Open-Source LLMs.DeepInfra is proud to announce that we have released "JSON mode" across all of our text language models. It is available through the "response_format" object, which currently supports only {"type": "json_object"}
Our JSON mode will guarantee that all tokens returned in the output of a langua...
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.© 2026 DeepInfra. All rights reserved.