Are you in the Weights?

About Are you in the Weights?

Are you in the Weights? is a free web tool that checks how strongly multiple AI language models recognize a given name. It queries several frontier and smaller models in parallel, then groups the responses to return a single recognition score. The name references the billions of parameters-the "weights"-that make up a model's training data.

Review

The tool does one specific thing: it tells you if a name appears to have been memorized by today's LLMs. Typing a name fires off parallel queries to models like Claude and Kimi, then clusters the answers into a visual and numeric indicator. It's a fast, curiosity-driven utility with no signup required.

Key Features

• Queries leading AI models simultaneously, not just one at a time.
• Clusters responses to produce a unified "recognition strength" metric.
• Covers both frontier-scale models and smaller, efficient ones.
• No authentication needed; results appear immediately.
• Free to use, with no usage caps announced as of launch week.

Pricing and Value

The product is free at launch. No payment plans, credits, or subscription tiers are listed. It's a one-page utility that does what it says without ads or required accounts.

Pros

• Shows how different AI models perceive a name in one view, instead of testing each model manually.
• Parallel querying makes the comparison quick, even across several models.
• Deliberately lightweight-it works on a basic browser without plugins.
• Includes both large, well-known models and less common ones, giving a range of perspectives.
• Transparent about the clustering method; the maker shares the approach in public comments.

Cons

• Results merge all interpretations of a name; it can't separate two people with the same name.
• The tool measures only name recognition, not factual depth or reasoning ability.
• Not well suited for individuals with very common names who want an accurate personal signal.

It's a handy check for AI practitioners, researchers, or anyone curious about what names live "in the weights." If your name is shared by many others, the clustering will produce an aggregate that may not reflect you individually. For one-off curiosity or lightweight model comparison, it does the job without friction.

Open 'Are you in the Weights?' Website