Speculative Decoding Patents: Who Leads, Where the Gaps Are 2026
Filing growth compares 2021 (458 records) with 2024 (548) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 15,242 records in scope (CR5), not by the ranked leaders only.
What the speculative decoding patent record shows
Speculative decoding accelerates large language model inference by having a smaller draft model propose several tokens ahead, which the target model then verifies in a single pass. The technique moved from research paper to patent filing quickly once inference cost became a commercial bottleneck for foundation model deployment, and the filing record reflects that: 15,242 published records sit within the search scope defined here, spanning general-purpose compute assignees as well as newer entrants building directly on top of large language model serving stacks. The representative filing from Snowflake, covering suffix-based speculative token decoding hybridised with a draft-model approach, illustrates where the frontier of claim drafting now sits — combining two prior distinct techniques into one system claim.
The concentration figures below describe who has staked the most claim territory, not who invented the technique first. Because publication lags filing by roughly 18 months, the most recent one to two years in any trend undercount actual filing activity and should be read as provisional rather than a sign of slowing interest.
Filing trend and technology composition
Two views of the same 15,242-record dataset: filings by year, and the IPC subclasses those filings carry.
A rising filing curve with a mid-decade peak
Filings ran from 497 in 2017 to a peak of 704 in 2020, before settling into a still-elevated band; 2021 to 2024 filings grew 20%, from 458 to 548. The 2025 and 2026 figures are undercounts because of publication lag, not evidence of a slowdown.
Software claims dominate the classification profile
G06F (electric digital data processing) appears on 80.7% of all records, far ahead of H04L (digital information transmission) at 8.0% and H04N (pictorial communication) at 5.7%. Because a single record can carry several IPC codes, these shares add up to more than 100% of the 15,242 records in scope — the pattern to note is how thin the presence of dedicated AI-model classification (G06N, 3.7%) still is relative to the general-purpose data-processing class.
Shares are the percentage of the 15,242 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Foundation Models: Speculative Decoding Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about foundation models: speculative decoding patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaA representative filing and the most-cited prior art
US12572745B1 — Suffix-based speculative token decoding for artificial intelligence model
The filing describes a hybrid speculative token decoding system that combines suffix-based decoding with a draft AI model approach, aimed at accelerating inference throughput while adapting to different workloads — particularly agentic applications with repetitive token generation patterns.Filed by Snowflake Inc., published 2026-03-10.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20090254572A1 | Digital information infrastructure and method | 2,827 |
| 2 | US20100250497A1 | Electromagnetic pulse (EMP) hardened information infrastructure with extractor, cloud dispersal, secure stora… | 1,777 |
| 3 | US20090249222A1 | System and method for simultaneous media presentation | 1,367 |
| 4 | US20110161076A1 | Intuitive Computing Methods and Systems | 1,137 |
| 5 | US8468244B2 | Digital information infrastructure and method for security designated data and with granular data stores | 1,137 |
| 6 | US20090216910A1 | Computing infrastructure | 1,027 |
| 7 | US6668325B1 | Obfuscation techniques for enhancing software security | 905 |
| 8 | US20110143811A1 | Methods and Systems for Content Processing | 834 |
| 9 | US20110219208A1 | Multi-petascale highly efficient parallel supercomputer | 828 |
| 10 | US20110098056A1 | Intuitive computing methods and systems | 768 |
High citation counts favour older, foundational filings inside this searched corpus — they signal influence on later filings, not current commercial relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
Put your own technology through the same analysis
Eureka on the web
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →MCP server & REST API
When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →What the numbers mean for a filing decision
Three findings from the assignee ranking, filing trend and classification data that matter more than the raw counts alone.
Half the field sits with a handful of filers
The top 5 assignees combined account for 50.5% of all 15,242 records in scope, and the top 10 extend that to 60.4%. That leaves a long tail of ranked entrants below tenth place holding comparatively thin portfolios, which is where freedom-to-operate risk is more fragmented and less predictable.
Filing activity is still climbing, not cooling
After peaking at 704 filings in 2020, annual filings dipped before recovering: 2021's 458 filings grew to 548 by 2024, a 20% increase over that span. Because publication lags filing by around 18 months, 2025 and 2026 figures will revise upward and should not be read as a decline.
The claim space is overwhelmingly general digital data processing
G06F covers 80.7% of the 15,242 records in scope, far ahead of digital transmission (H04L, 8.0%) or AI-model-specific classification (G06N, 3.7%). Filers are largely drafting speculative decoding as a general computing-architecture claim rather than routing it through AI-model-specific classification, which affects where examiners and competitors will look for prior art.
Filing activity concentrates heavily in the US
The United States receiving office accounts for 8,316 records, well ahead of Europe (EPO) at 1,756 and WIPO/PCT filings at 1,310. A filer targeting only US protection is following the dominant pattern, but the EPO and PCT volumes indicate meaningful parallel activity worth tracking for multi-jurisdiction strategy.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to foundation models: speculative decoding patent landscape, with the prior art for and against each one.
Where to take this analysis
The dataset points to a few concrete next steps for teams evaluating freedom to operate or drafting new claims in this space.
Check freedom-to-operate against the concentrated top 10
With 60.4% of all 15,242 records held by the top 10 ranked assignees, any new filing in core speculative decoding architecture should be checked against those portfolios first before broader searching.
Run a freedom-to-operate checkTrack the G06N gap as AI-specific classification grows
Only 3.7% of records carry a dedicated AI-model IPC classification against 80.7% under general digital data processing — a gap likely to narrow as classification practice catches up with the technology.
Monitor emerging classification shiftsWatch post-2024 filings as they publish
Because publication lags filing by roughly 18 months, the 2025–2026 filing counts shown here will continue to rise; revisit the trend periodically rather than treating the current curve as final.
Set up ongoing monitoringCommon questions about speculative decoding patents
Speculative decoding is an inference-acceleration technique where a smaller draft model proposes several candidate tokens ahead of the main model, which then verifies them in a single pass instead of generating one token at a time. It matters commercially because inference cost and latency are major bottlenecks for deploying large language models at scale, so a technique that cuts inference time translates directly into lower serving costs. That commercial pressure is reflected in the filing record, which spans 15,242 published records and a filing trend that grew from 458 filings in 2021 to 548 in 2024, a 20% increase.
The assignee ranking covers 100 companies, and filing activity is concentrated at the top: the five leading assignees together hold 50.5% of all 15,242 records in scope, and the top 10 hold 60.4%. This means roughly 90 further ranked entrants share the remaining 40% of the field, a long tail worth checking individually if you are assessing collision risk outside the largest portfolios. The ranking includes both long-established semiconductor and computing companies and newer entrants building directly on foundation-model serving infrastructure.
Filings peaked at 704 in 2020 and the confirmed trend through 2024 shows continued growth, up 20% from 458 filings in 2021 to 548 in 2024. Figures for 2025 and 2026 appear lower in the raw count, but that reflects publication lag of roughly 18 months rather than a genuine slowdown — those years' filings are still being published and will revise upward. Treat any apparent dip in the most recent one to two years as incomplete data, not a trend reversal.
The dominant classification is G06F (electric digital data processing), present on 80.7% of the 15,242 records in scope, reflecting that most filers frame speculative decoding as a general computing-architecture claim. Secondary classes include H04L (digital information transmission) at 8.0%, H04N (pictorial communication) at 5.7%, and G06N (AI-model-specific computing) at only 3.7%. Because a record can carry multiple IPC codes, these percentages add up to more than 100% of the record total, and the low G06N share suggests dedicated AI-model classification has not yet caught up with how the technology is actually being filed.
The United States receiving office accounts for the largest share of filings at 8,316 records, well ahead of the European Patent Office at 1,756 and WIPO/PCT filings at 1,310, with the United Kingdom, Germany, and Australia each carrying smaller but non-trivial volumes. A filer seeking primarily US protection is following the dominant pattern in this dataset, but the meaningful EPO and PCT volumes indicate that competitors are pursuing multi-jurisdiction coverage, which is worth factoring into any filing strategy that expects to compete globally.
Research Foundation Models: Speculative Decoding Patent Landscape in depth with Eureka
Go past this page: query the whole foundation models: speculative decoding patent landscape corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.