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What you can do with Dynolab

Dyno Lab is a free, open-source Mac app for running local AI models and investigating their behavior with activations, probes, SAEs, interventions, agent tests, and a Python SDK, HTTP API and MCP bridge.

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Authorization notice. This tool is dual-use. Only use it on software, sites and systems you own or have explicit permission to test, and follow the relevant licenses and terms of service.

What do you want to do?

5 use cases

  • Run Claude Code or Codex on a model you own

    Launch Claude Code or Codex so the model answers on your Mac instead of a vendor server.

    View prompt
    In the canivel/dynolab repo, read docs/coding-tools.md and launch Claude Code on the downloaded model <model-name> with `dyno launch claude --model <model-name>`. Expected output: a Claude Code session that answers a simple prompt using the model served on this Mac. Verify that the session replies and that the model is the one you started in Dyno Models.

  • Test whether an agent breaks a rule to reach a goal

    Set up a team sandbox test and read the Observer report on who broke what.

    View prompt
    In the canivel/dynolab repo, read docs/agent-sandbox-tests.md and use the Dyno Assistant to draft a team sandbox test for the goal <goal-description>. Expected output: a setup in Agents → Setup with a lead agent, teammates and an Observer. Verify that nothing runs or saves until you approve it.

  • Reproduce the identifier-fidelity probe experiment

    Rerun the saved Qwen3.8 probe and compare it with the token-count baseline.

    View prompt
    In the canivel/dynolab repo, follow examples/identifier-fidelity-probe/README.md to run the saved probe on the model <model-name>. Expected output: held-out probe metrics next to the input-only control baselines. Verify that your numbers are reported as an exploratory robustness check, not as a validated safety monitor.

  • Keep a local notebook of a research question

    Store prompts, results and observations for one question in Lab → Studies.

    View prompt
    In the canivel/dynolab repo, read docs/research-notebooks.md and create a study for the question <question>. Expected output: a saved study with prompts, results and observations in Lab → Studies. Verify that any token-limited or incomplete run is shown as incomplete, not as an answer.

  • Script repeat experiments with the Python SDK

    Run saved experiments from code and collect results as jobs and artifacts.

    View prompt
    In the canivel/dynolab repo, read docs/sdk-guide.md and write a Python script that submits an activation job for the model <model-name>. Expected output: a job result and its saved artifacts. Verify the artifact paths and that the job finished without error.

How to use Dynolab

  1. Check you have what it needs: An Apple Silicon Mac running macOS 14 or later; The Dyno app downloaded from the latest GitHub release; An MLX model downloaded through Discover in the app.
  2. Open canivel/dynolab on GitHub and read the README and license.
  3. Download the Apple Silicon DMG from the latest release, open it and drag Dyno into Applications.
  4. Open Dyno, download an MLX model in Discover, then select and start it in Models.
  5. Run dyno launch claude --model qwen3.8-27b (replace the model name with one you have downloaded).
  6. Or run dyno launch codex --model qwen3.8-27b to use Codex instead.

These steps come from our top use case, Run Claude Code or Codex on a model you own, which also has a copy-paste agent prompt.

Dynolab alternatives · Best AI repos for Research

About this repo

  • Who it is forBuilt for AI safety and interpretability researchers and developers on Apple Silicon Macs who want to test model behavior locally.
  • Why it is hot
  • LanguageSwift
  • Sourcegithub.com/canivel/dynolab · Back to Hot repos

Requirements

  • An Apple Silicon Mac running macOS 14 or later
  • The Dyno app downloaded from the latest GitHub release
  • An MLX model downloaded through Discover in the app
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Questions about Dynolab

What is Dynolab?

Dyno Lab is a free, open-source Mac app for running local AI models and investigating their behavior with activations, probes, SAEs, interventions, agent tests, and a Python SDK, HTTP API and MCP bridge. It is an open-source project on GitHub: https://github.com/canivel/dynolab.

Who is Dynolab for?

Built for AI safety and interpretability researchers and developers on Apple Silicon Macs who want to test model behavior locally.

What can I do with Dynolab?

5 use cases so far, for example: Run Claude Code or Codex on a model you own; Test whether an agent breaks a rule to reach a goal; Reproduce the identifier-fidelity probe experiment. Each has steps and a copy-paste agent prompt.

What do I need to run Dynolab?

An Apple Silicon Mac running macOS 14 or later; The Dyno app downloaded from the latest GitHub release; An MLX model downloaded through Discover in the app.

What are alternatives to Dynolab?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Dynolab safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.