Ollama v0.35.1-rc1 Released: Adds Support for the Clef Model

Ollama, the popular local LLM runner, has released its latest release candidate: v0.35.1-rc1. As an open-source project with over 180,000 stars on GitHub, every new version from Ollama draws close attention from the local AI deployment community.

What's New in This Release

According to the official release notes, the primary change in v0.35.1-rc1 is the addition of support for the Clef model (corresponding to PR #18741), tagged by project maintainer jmorganca. The release has been verified with a GitHub GPG signature (GPG key ID: B5690EEEBB952194), confirming it as an official, trusted release.

It's worth noting that the rc1 suffix indicates this is a Release Candidate — meaning it's still in the pre-release testing phase. Developers eager to try out new features are welcome to experiment with it, but deploying it in production environments is best held off until the stable version is available.

Clef is a multimodal model designed for audio understanding. It can process audio input and generate text descriptions or answer questions about audio content. Unlike mainstream text-only or vision-language multimodal models, Clef brings audio perception capabilities into the large language model framework — placing it in the niche category of Audio-Language Models. With Ollama now supporting Clef, the local deployment community can, for the first time, run an audio-capable model on personal devices through Ollama's unified interface — without needing to build a complex audio inference environment from scratch. This has practical implications for use cases like local voice assistants, audio content summarization, and sound classification.

Why Expanding Model Support Matters

The core value of Ollama lies in enabling users to conveniently run a wide variety of open-source large language models locally. Each newly supported model expands the library of options available to users and reflects the project's ongoing commitment to ecosystem compatibility.

For local deployment scenarios, model compatibility directly defines the practical boundaries of a tool. Ollama abstracts away the differences in underlying formats across models through a unified interface, so developers don't need to handle loading and inference logic separately for each model. The addition of Clef support is yet another example of this compatibility capability continuing to grow.

Internally, Ollama uses GGUF (GPT-Generated Unified Format) as the standard format for model storage and loading, with llama.cpp as the underlying inference engine. When a new model is "supported," it means Ollama has completed the GGUF conversion adaptation for that model's architecture and verified its correctness within the llama.cpp inference framework. This is no small feat — different models vary in architectural details such as attention mechanisms, positional encodings, and activation functions, and each new architecture requires dedicated implementation at the inference engine level. So every newly supported model represents a meaningful amount of low-level engineering work, not just a configuration-level integration.

Ollama's Place in the Ecosystem

As a leading tool for running LLMs locally, Ollama has built a massive user base — 182k stars and 18.1k forks speak to its high activity level within the developer community. It lowers the barrier to running large models locally, allowing everyday developers to deploy and call models on their own devices without complex setup.

Frequent version releases are a direct indicator of an open-source project's vitality. Based on the cadence of this release candidate update, the Ollama team maintains a high level of development activity, continuously responding to community needs and changes in the model ecosystem through rapid minor releases.

Summary

v0.35.1-rc1 is an incremental update focused primarily on expanding model support, with the key addition being Clef model compatibility. Developers following local AI deployment can keep an eye on the upcoming stable release before deciding whether to upgrade. Since this is a release candidate, it is advisable to exercise caution before using it in any business-critical environment.