Long Context Attention Patents: Who Leads, Where the Gaps Are 2026
Long Context Attention Mechanisms Patents
Concentrated at the top. The five leading filers together account for 31.5% of all 305 records in scope, with the leader alone holding 49 filings. Annual filings sat near zero through 2017 and climbed slowly until 2021, when 19 records were filed. By 2024 – the most recent year that can be treated as complete – that figure had reached 67, a +253% rise over three years. 2025 shows 113 filings, the peak so far, but because publication trails filing by around 18 months, 2025 and the partial 2026 count of 27 should be read as still filling in rather than as a plateau or decline.
- 1GOOGLE LLC16.1%
- 2QUALCOMM INC4.3%
- 3NVIDIA CORP3.9%
- 4GDM HOLDING LLC3.6%
- 5ATTENTION LABS INC3.6%
See the full long context attention mechanisms analysis in Eureka
- The complete ranking, not just the top five
- Every IPC branch with its share of the corpus
- The most-cited records, and where claim space is still thin
Common questions about this landscape
Who holds the most patents in long context attention mechanisms?
The dataset’s assignee ranking shows a single leader holding 49 of the 305 records in scope, well ahead of the rest of the ranked entrants. The top five assignees combined hold 31.5% of all records, and the top ten hold 45.2%, indicating that a small group of large technology and chip companies files far more than the median entrant. Below tenth place, filing counts drop quickly into single digits, forming a long tail of organisations with only one or two filings each.
Is patent filing in this area still growing?
Yes, through the last complete year of data. Annual filings rose from 19 in 2021 to 67 in 2024, a +253% increase over three years, reflecting the industry’s push toward longer context windows in deployed models. Figures for 2025 and 2026 appear higher still, but because publication typically lags filing by about 18 months, those years are undercounted and should not be read as a plateau or a slowdown.
What does it mean that most patents fall under IPC class G06N?
G06N covers computing arrangements based on specific computational models, which in practice means machine-learning and AI architectures. That class appears in 70.5% of the 305 records in scope, meaning most applicants are framing their attention-mechanism inventions as model-level or algorithmic contributions rather than as generic data-processing improvements. G06F, the general digital-data-processing class, appears in 36.7% of records, often alongside G06N on the same filing since a record can carry multiple classes.
Disclaimer. This analysis is based on Patsnap Eureka data drawn from a limited snapshot of global patent records and is provided for general information and reference only. Patent data carries inherent limitations — recent filings are under-counted because of publication lag, counts may be on a record or family basis, classification and applicant-name data may contain errors or duplicates, and the underlying search query defines the scope shown — so the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing here is an exhaustive prior-art, novelty, freedom-to-operate or validity search, nor does it constitute legal, financial or professional advice, and it should not be relied upon as such. Verify independently and review with qualified patent and legal professionals before acting on it.
Method: Filing trend and technology composition. Derived from a Patsnap search on Long Context Attention Mechanisms covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish. Every share divides by all records in scope. Data: Patsnap Eureka. See the full landscape report.