Realtime AI News
Baseten joins Hugging Face Inference Providers, opening access to Kimi K3, DeepSeek V4 Flash and GLM-5.2
Hugging Face announced that Baseten is now a supported Inference Provider on the Hub, expanding serverless inference available directly on model pages. The initial integration covers conversational and text-generation tasks, giving developers access to open-weight LLMs such as Kimi K3, DeepSeek V4 Flash and GLM-5.2 through Hugging Face SDKs and agent harnesses.
Hugging Face announced on August 6 that Baseten is now a supported Inference Provider on the Hugging Face Hub, broadening the serverless inference options available directly on model pages.
Baseten is an AI infrastructure platform covering serverless AI, training and more, with a catalog of frontier models. In this initial integration, it launches support for conversational and text-generation tasks on Hugging Face, enabling access to popular open-weight LLMs such as Kimi K3, the latest DeepSeek V4 Flash and GLM-5.2, with additional task types rolling out soon.
Inference Providers are integrated into Hugging Face's client SDKs — huggingface_hub (>= 1.26.1) for Python and @huggingface/inference for JavaScript — so developers can route requests to Baseten-hosted models using a Hugging Face token.
Two calling modes are available: with a custom key, requests go directly to the inference provider and are billed on the provider's account; with HF routing, no provider token is needed and charges are applied to the HF account at standard provider rates, with no markup.
Hugging Face notes that Inference Providers are integrated into most agent harnesses, including Pi, OpenCode, Hermes Agents and OpenClaw, meaning Baseten-hosted models can plug straight into popular developer tools without extra glue code.
HF PRO users get $2 worth of Inference credits every month, usable across providers.
For developers, Baseten's arrival adds another serverless inference backend to model pages and SDKs, making open-weight models like Kimi, DeepSeek and GLM easier to call from existing workflows.
Why it matters
Baseten joining Hugging Face Inference Providers widens the serverless inference channels for open-weight models, lowering the barrier for developers to integrate frontier open-source LLMs.
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