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Ollama has released v0.34.0, adding a way to use Ollama models directly in ChatGPT Desktop. The release also updates several parts of its OpenAI-compatible interface. The announcement is documented in the v0.34.0 release notes.
Setup is available through the Ollama app on MacOS. The update also improves structured output performance on Apple Silicon, adds support for client tool search and response compaction, and fixes image handling through compacted responses.
For people making things, the main change is workflow flexibility. You can keep using ChatGPT Desktop as the place where you write prompts, review responses, and work through a project, while selecting Ollama models for supported tasks. That reduces the need to move text between separate applications or build a custom interface before testing an open model.
The release is especially relevant for creators who already use structured output. Structured output is useful when a model needs to return predictable fields instead of free-form prose. A content pipeline might ask for a title, summary, tags, and scene list in a fixed format. A design tool might request layout values or a list of assets. Better performance on Apple Silicon should make those interactions more responsive on compatible Mac hardware, although the announcement does not provide benchmark results.
The OpenAI-compatible updates are useful for developers building around a common client interface. Tool search can help a client find or select tools during an interaction. Response compaction is intended to reduce the amount of conversation context that must remain active as a session grows. Together, these additions matter when a project involves repeated model calls, external actions, or long-running sessions. They may also make it easier to test an Ollama-backed workflow without rewriting every integration around a different API shape.
Image support is another practical detail. The release notes say images now work correctly through compacted responses. That matters for applications that combine visual inputs with longer conversations. For example, a maker could keep an image review session going while the system compresses earlier context, rather than treating image handling as a separate path that may break when the response is compacted.
On Mina Labs, Ollama v0.34.0 is available for 8 per image. That gives makers a direct way to try the release from the platform rather than setting up a local environment first. The listing is the useful starting point if you want to evaluate the model behavior, test a prompt flow, or compare the output with an existing project. The price token refers to one image; the release itself includes broader text, tool, and client-integration changes.
We would use this release first for structured creative briefs. A prompt could request a fixed object containing a project concept, target audience, visual direction, shot list, and production notes. The resulting fields could then feed a second step in a workflow. The performance improvements on Apple Silicon would be useful when iterating over many versions of the same brief locally.
We would also test it for image-aware review sessions and tool-driven production tasks. An image could be submitted for analysis, followed by requests for alternate compositions, captions, or asset metadata. Tool search and response compaction could support a longer session where the model needs to find an available action and retain the important decisions from earlier turns. These are practical tests for the release because they exercise the specific areas Ollama has changed: structured output, compatible clients, compacted responses, and images.