Question 1

What is the Gecko Mindshare Index (GMI)?

Accepted Answer

The Gecko Mindshare Index tracks what percentage of total AI attention each model, agent, company, and person commands across Reddit, Twitter/X, Hacker News, GitHub, arXiv, and news outlets. A GMI of 92 means the entity is in the elite tier of attention. All weights are published at /mindshare/methodology.

Question 2

What is the Pulse Score?

Accepted Answer

The Pulse Score measures overall AI ecosystem attention on a 0-100 scale. The current reading is 78/100 (rising), up 12 points over the past week. Higher scores indicate more total conversation volume and engagement across all tracked sources.

Question 3

Which AI model has the most mindshare right now?

Accepted Answer

GPT-5 Chat leads with 18.5% of total model mindshare. The biggest 7-day gainer is Claude Mythos Preview (+520bps), while GPT-5 Chat saw the largest decline (-340bps).

Question 4

How is mindshare different from benchmarks?

Accepted Answer

Mindshare measures attention and conversation volume. Benchmarks measure technical performance. The Hype vs Reality chart overlays both to show which models are overhyped (high attention, lower scores), underrated (strong scores, low attention), or have deserved recognition (both high).

Question 5

What does the attention premium mean for companies?

Accepted Answer

The attention premium compares a company's share of AI mindshare to its share of AI market cap. A premium above 1.0 means the company gets more attention than its economic size warrants (overexposed). Below 1.0 means it flies under the radar relative to its value.

Question 6

How much mindshare do open-source models have?

Accepted Answer

Open-source models (DeepSeek, Qwen, Llama, Yi, Falcon, and others) collectively hold 18.3% of total model mindshare. This share has been growing steadily as community fine-tunes and local deployment drive sustained interest.

Question 7

What sources does Gecko Mindshare track?

Accepted Answer

Gecko Mindshare aggregates signals from 6 sources: Reddit (r/LocalLLaMA, r/MachineLearning), Twitter/X, Hacker News, GitHub (stars, forks, issues), arXiv (papers, citations), and tech news outlets. Each source is weighted by signal quality and lead/lag characteristics.

Question 8

How often is mindshare data updated?

Accepted Answer

Mindshare scores are updated daily from public signal sources. The Pulse Score, Weather Report, and Power Rankings refresh each day. Historical snapshots are stored weekly for trend analysis.

Source	Volume	Sentiment	Lead/Lag	Description
Reddit	35%	52%	Follower	Deepest discussion. r/LocalLLaMA, r/MachineLearning, r/artificial. Follows Twitter by 6-12h but with much deeper analysis.
Twitter / X	28%	45%	Leader	Fastest signal. KOL amplification drives narrative. High volume, mixed signal-to-noise. Breaking news appears here first.
Hacker News	15%	48%	Follower	Technical depth. Strong engineering bias. Front page stories drive 24h attention spikes. Comment quality highest of all sources.
GitHub	12%	62%	Lagging	Revealed preference signal. Stars, forks, and issue velocity show what developers actually use vs. what they talk about.
arXiv	5%	58%	Leading	Research frontier. Paper submissions and citations predict which models will matter in 3-6 months. Low volume, high signal.
News	5%	40%	Lagging	Mainstream coverage. TechCrunch, The Verge, Bloomberg, Reuters. Follows social media by 12-48h. Amplifies narratives to non-technical audience.

Signal Sources · Tracked

Source Volume Comparison

Source Quality Matrix

Data Sources

Sources FAQ

Mindshare

Data

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