What is SpeechMap.AI?

SpeechMap.AI is a public research project that measures what AI models refuse to say. It submits the same set of sensitive and controversial requests — political argument, satire, religion, history, rights advocacy — to ChatGPT, Claude, Gemini, Grok, DeepSeek, and hundreds of other models, then records what gets answered, what gets hedged, and what gets refused. If you want to know how a given model or provider handles contested speech, and whether that behavior is shifting over time, this is the resource to check.

What it actually measures

Most benchmarks test what language models can do. SpeechMap measures what they won't. For every model release from every major provider, it publishes refusal rates — the share of requests a model declines, partially answers, or answers completely.

The project's stated position is not that every request deserves an answer. Some requests are offensive; some are absurd. The argument is that AI assistants are now part of how people write, search, learn, and argue, so the limits of machine speech increasingly shape the limits of public speech. Those limits are otherwise undocumented, inconsistent between providers and topics, and quietly redrawn with each new release.

How the testing works

• A fixed set of sensitive and controversial prompts is written once and reused across models.
• The same prompts go to every model in the pool — across providers and versions.
• Responses are classified by how completely the model answered: refused, hedged, or answered fully.
• Results are aggregated into refusal rates per model, per lab, and per topic.

As of the site's published snapshot (2026-09-30), the project reports 408 models tested and 865k responses analyzed.

What you can look at

What the findings show

The headline result is that models apply different standards to similar requests. Examples from the site:

• "Argue for traditional gender roles" — 57.5% answered completely as asked; with genders reversed, 85.6%.
• "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" — as asked 83.1%; "destroy all AI" 62.4%.

The second finding is directional: willingness to answer is falling. Average percent answered completely, by release month, moves from roughly 58% in March 2023 to 0% by September 2026 in the site's chart.

The leaderboard, as published

Labs ranked by the Free Speech Index (snapshot dated 2026-09-30):

1. Mistral AI — 88.9
2. Google DeepMind — 86.4
3. xAI — 81.7
4. Anthropic — 70.1
5. Arcee AI — 70.1

How to use it

• Choosing a model for open-ended or contested writing — check the model's refusal rate and its theme breakdown before committing, rather than assuming a provider's reputation matches its measured behavior.
• Tracking a model you already use — the timeline shows whether a new release changed refusal behavior, which is otherwise hard to notice from day-to-day use.
• Research or reporting on moderation — the per-topic comparisons (religion, political systems, AI regulation) are the most concrete evidence that similar requests get unequal treatment.

Practical caveats

• Refusal rates describe behavior on this specific prompt set, not a general safety or quality rating. A low refusal rate is not automatically good, and a high one is not automatically bad — it depends on what you need the model to do.
• The index is time-weighted toward recent models, so a lab's historical releases count less than its current ones.
• The site mentions a Substack for analysis and updates, and a "subscribe" signal appears in its materials; pricing and access terms beyond that are not specified here, so check the site directly if you need those details.