Which agents work with it?

Any agent that reads skills from a directory. Claude Code, Codex, Antigravity CLI and Grok Build all read /present natively.

What does “free and unlimited” mean?

Generating presentations is free with no cap. Narration runs on your own machine, so there's nothing to meter.

Where does the narration run?

On your machine. The finished presentation publishes to your channel so anyone with the link can watch it.

Do I have to write slides?

You never touch slides. You ask — “brief me on what shipped overnight” — and your agent authors, narrates, and publishes.

Every presentation gets a watch link on your channel. Send the link; it plays in any browser, phones included.

Yes — the /present skill is MIT-licensed, and the authoring spec is public.

Ollama v0.33.1

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Ollama v0.33.1 is out. Claude on your Mac now talks to your local models, the MLX runner enforces JSON schemas, and large models load from slow disks without failing.

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Ollama v0.33.1

Ollama v0.33.1 is out. Claude on your Mac now talks to your local models, the MLX runner enforces JSON schemas, and large models load from slow disks without failing.

01 Claude, running on your models

Claude, running on your models.

Turn Claude on inside Ollama

Open Ollama, go to Apps, and switch Claude on. If Claude isn't installed on your Mac, Ollama downloads it and finishes the install for you.

You choose which model answers

In Ollama Settings, under Apps, pick an Ollama model for each Claude model option, then restart Claude. One model can cover more than one option.

What Claude keeps when it runs on Ollama

Claude keeps its own features here. Subagents split a big task up, web search comes through Ollama's own search, Cowork handles the long jobs, and auto mode decides when to ask you.

Switching it off puts Claude back

Turn Claude off in Apps and Ollama restores the configuration Claude had before. Quitting Ollama does the same thing. If Claude is open, Ollama asks to restart it.

The suggested pairings come from Ollama’s servers

The pairings Ollama suggests for each Claude model now come from Ollama's servers instead of a list baked into the app. So new recommendations reach you without an update.

The model picker holds its place

Picking a model in Settings used to jump the page. The picker was rebuilt on a popover, so the list opens where you left it and the scroll position stays put.

02 The MLX runner

The MLX runner.

A JSON schema is now enforced, not just accepted

Ask the MLX runner for JSON and it used to hand back ordinary text. Now a grammar masks every sampling step, so each token it emits fits your schema.

What the constraint costs you

Constrained generation runs as fast as generating without a draft model. Speculative decoding is switched off while a schema is active, and that is the whole difference in speed.

Big models load off slow disks

Loading a large model off a slow volume used to abort with a command buffer failure. Metal was waiting on file reads, so the weights are now read on the CPU first.

03 Models and machines

Models and machines.

Qwen3.8 Flash Next runs on MLX

Qwen3.8 Flash Next now runs on Apple silicon through the MLX engine. Ollama added the architecture, its image tower, and the import step that shrinks its largest weights.

gemma3 stays where it can see images

The MLX port of gemma3 handled text only. Ollama removed it, so gemma3 keeps running on llama.cpp, where it can still look at your images.

Pi follows OLLAMA_HOST to a remote server

Ollama can launch the Pi coding agent. It kept whatever server address it had saved, so pointing OLLAMA_HOST at a remote machine did nothing. The launcher now rewrites it.

Under the hood

Both inference engines moved up a version, llama.cpp to build b10630. And the Linux Docker build, which broke on a missing file, works again.

Update to v0.33.1

That is Ollama v0.33.1. Update from ollama.com, or let the app update itself.