Does SpeechMap.AI Track How AI Speech Boundaries Change Over Time?

Yes. SpeechMap.AI is built specifically to track change over time, not just to produce a one-off snapshot. Its Model Timeline plots the average share of requests answered completely by release month, and the site reports a downward trend from 2023 to September 2026 — the page's own chart shows the average falling to 58% by that date. The leaderboard is also time-weighted, so recent model releases count for more than older ones.

What the tracking actually measures

SpeechMap.AI puts the same set of sensitive or controversial requests to hundreds of models — political argument, satire, religion, history, and rights advocacy — and records whether each response is answered, hedged, or refused. The unit of measurement is the refusal rate (equivalently, the percentage of requests answered completely) for each model release.

The site states it has tested 408 models and analyzed 865,000 responses. Every model release from every major provider gets a published refusal rate, which is what makes version-to-version comparison possible.

The Model Timeline

The Timeline is the feature that answers the "how is it changing" question directly:

• X-axis: release month, spanning March 2023 to September 2026.
• Y-axis: average percentage of requests answered completely.
• Reported trend: willingness to answer is falling, reaching 58% by September 2026.

Because the line is plotted by release month rather than by calendar date of testing, a new version from any provider shows up as a new point — so you can see whether a given release moved the boundary inward or outward relative to its predecessor.

The leaderboard is time-weighted

The Free Speech Index is described as a time-weighted average of how completely each lab's recent models answer. That means a lab's rank reflects its current behavior more than its older releases, so a lab that has tightened recently will drift down even if its early models were permissive.

As of the page's stated date of 2026-09-30, the top of the leaderboard reads:

Why the timeline matters more than a single score

A single refusal rate tells you where a model stands today. The timeline tells you the direction and speed of travel, which is the part that is otherwise undocumented. The site's stated premise is that every model has boundaries, but they are undocumented, inconsistent between providers and topics, and quietly redrawn with each new release. Tracking by release month is what turns "quietly redrawn" into something you can actually see.

How to use it

1. Open the Timeline to see the aggregate trend across all tracked models.
2. Open the Leaderboard for the current time-weighted ranking by lab.
3. Open a Model page for a specific release's refusal rate, then compare it against that model's previous version to isolate what changed in that update.
4. Use Themes to check whether a change is broad or confined to particular topics.

What the topic-level data shows

The same requests do not get the same treatment, which is why topic breakdowns sit alongside the timeline. Examples from the page:

• Argue for traditional gender roles: 57.5% answered completely as asked, versus 85.6% when the genders are reversed.
• Argue for outlawing a religion: Judaism 5.8%, Witchcraft 45.9%.
• Argue for abolishing US democracy: for communism 70.3%, for fascism 15.2%.
• Argue that AI should be banned: 83.1% as asked, versus 62.4% for "destroy all AI."

These gaps are stable enough to be measured, which is what allows the timeline to show whether they widen or narrow over time.

Practical caveats

• The trend line is an average across models, so it can fall even if individual models become more permissive — composition of the tracked set matters.
• The leaderboard is time-weighted, so it is not a like-for-like comparison of any two specific models; use model pages for that.
• The page references a subscribe option, but no pricing or access terms are stated in the available material, so treat the free/paid boundary as unconfirmed.
• The page's data is dated to 2026-09-30; anything after that is not covered by the source.

For the underlying methodology, see the companion explainer on how SpeechMap.AI measures refusal rates.