DeepInfra raises $107M Series B to scale the inference cloud — read the announcement
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 one is restrictive for our use cases.
Forking the project
We decided to fork the project and continue to maintain it under the Apache 2.0 license. We will continue to contribute to the project and keep it up to date. We will accept pull requests from the community, and we will keep the project truly open source and free to use.
Here is a link to the code: https://github.com/deepinfra/text-generation-inference
We hope that in time a community of other developers and organizations that want to keep this project truly open source will form around it.
License changes mid-flight
Sadly it is becoming more and more common for popular open source projects to change their license after they gain some traction. This happened with MongoDB, Grafana, ElasticSearch, and many others. As a developer, when you decide to adopt a particular open source project, you start investing time and effort into using it. You build your application around it, and you start depending on it. Then, suddenly, the license changes, and you might be forced to find an alternative.
Imagine if meta changes the license of pytorch. Or if tomorrow huggingface decides to change the license of transformers in a similar way to prohibit commercial use.
We believe that the changing of the license of open source projects mid-flight is a unfriendly move towards the community.
If you need any help, just reach out to us on our Discord server.
Qwen3.5 35B A3B API Benchmarks: Latency, Throughput & Cost<p>About Qwen3.5 35B A3B Qwen3.5 35B A3B is a native vision-language model released by Alibaba Cloud in February 2026. It uses a hybrid architecture that integrates Gated Delta Networks with a sparse Mixture-of-Experts model, achieving higher inference efficiency. With 35 billion total parameters and only 3 billion activated per token through 256 experts (8 routed […]</p>
Kimi K2.6 API Benchmarks: Latency, TPS & Cost Analysis (2026)<p>About Kimi K2.6 Kimi K2.6 is an open-source frontier model from Moonshot AI, released on April 20, 2026. It is a native multimodal agentic model built for long-horizon coding, autonomous execution, and swarm-based task orchestration. The model uses a Mixture-of-Experts (MoE) architecture with 1 trillion total parameters and 32 billion activated parameters per token, using […]</p>
Qwen3.5 122B A10B API Benchmarks: Latency, Throughput & Cost<p>About Qwen3.5 122B A10B Qwen3.5 122B A10B is Alibaba Cloud’s mid-tier multimodal foundation model, released in February 2026. It is a multimodal vision-language Mixture-of-Experts model supporting text, image, and video inputs, designed for native multimodal agent applications. It features 122 billion total parameters with 10 billion activated per token through a hybrid architecture that integrates […]</p>
© 2026 DeepInfra. All rights reserved.