Qualcomm · Filed Dec 4, 2025 · Published Nov 5, 2026

Qualcomm Patents a Shortcut to Make Phone Chatbots Answer Sooner

Before a phone chatbot says a single word back to you, it has to read your whole question. Qualcomm's filing splits that reading into its own lighter pass and saves the costly word-picking step for the end.

Key processing units on a smartphone chip that run mobile artificial intelligence programs. Drawing from patent filing US 2026/0350403 A1.
Key processing units on a smartphone chip that run mobile artificial intelligence programs.
See all 13 drawings from this filing ↓
Publication number US 2026/0350403 A1 US20260350403A1
Applicant QUALCOMM Incorporated
Filing date Dec 4, 2025
Publication date Nov 5, 2026
Inventors Wenhao ZHANG, Zhiguo LI, Xinglong LIANG
US classification 706/15
Status when we published Waiting for an examiner (Aug 6, 2026)
Parent application is a National Stage Entry of PCTCN2023135355 (filed 2023-11-30)
Document 18 claims

What Qualcomm's two-part chatbot split does

You're typing a long question into a chatbot on your phone, and then you wait. The phone has to read every word of what you wrote before it can start replying, and on a small device that reading takes a while.

Qualcomm's filing describes a way to trim that wait. It splits the chatbot's model into two parts. The first part reads your question one small piece at a time and jots down notes about each piece. The second part, which does the actual word-picking for the reply, only switches on once the reading is done. The reading stage skips the word-picking machinery entirely.

Those notes are kept, so if you ask a follow-up question, the phone can pick up where it left off instead of re-reading your whole conversation.

From the filing · CLAIM 1
… determine, by a first language model, a first internal state for each of the first set of input tokens; and process, by a second language model, responsive to the first internal state being determined for all of the first set of input tokens, the first set of input tokens and the first internal state for each of the first set of input tokens …

Translation: One AI model processes the input text first, and then hands its internal data directly to a second model to speed things up.

How the prompt gets read before any word is picked

Chatbots read your text as tokens, small chunks that average about four characters. As the model works through them, it keeps a running record called the internal state, or KV cache (a stored set of notes on what it has already read).

The filing splits the model in two. Part 1, the decoder layers (the core number-crunching steps), loops through your tokens one at a time and builds the notes for each. It skips the LM head, the final stage that turns the model's internal numbers into an actual word.

When the last token is in, the tokens and notes go to Part 2, which includes the LM head and generates the reply. For a follow-up message, the loop runs on the new text, and the earlier notes and reply tokens are joined with the new ones before Part 2 runs again.

The description contrasts this with padding every prompt to a fixed length, which took an example 2.2 seconds regardless of your question's size, partly because some phone neural processors only accept fixed-size inputs. The token-at-a-time loop scales with your prompt, at an example 100 milliseconds per token.

From the filing · THE ABSTRACT
A processor-implemented method of accelerating prompt inferencing of large language models includes receiving a first input prompt.

Translation: The patent describes a new way to make large artificial intelligence models respond to users much faster.

Why on-phone AI replies could start sooner

If you've used an AI assistant on a phone, you know the wait before the first word shows up. The filing's goal is to cut that delay, which it says hurts the user experience, especially on small devices that have far less computing room than a data center.

The setup is described on a system-on-a-chip (one chip holding the CPU, graphics processor, neural processor and 5G modem), hardware found inside smartphones. That fits a company that sells phone chips, since faster AI replies make a phone look better. The filing gives no before-and-after timing for the new approach, so the size of the gain stays unknown.

Qualcomm's 14th entry we've tracked in AI assistants and agents since June joins earlier work on glasses that log what you see and phones routing AI queries.

Editorial take

The path to a product here is short. The filing describes no new hardware, only a reshuffling of work inside the software that runs a chatbot on a phone's existing chips.

What has to exist first is a chatbot model cut into two halves that hand notes to each other, plus software willing to run them in that order. That layer is software, so it can be tested without waiting on new silicon. If the reading-first split saves time, it could reach people as a faster first word and a speedier follow-up, with no new feature to point at.

The catch is proof. The filing offers example timings for the older approaches and none for this one, and the claims are broad. Call it a sensible, modest tweak: useful if it works on your phone, and easy to miss if it does.

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The drawings

13 drawing sheets from US 2026/0350403 A1 · click any drawing to enlarge

Phone processor parts and a fully wired neural network, drawing sheet 1 from US 2026/0350403 A1
Sheet 1 Phone processor parts and a fully wired neural network
Grouping visual connections to analyze images more efficiently, drawing sheet 2 from US 2026/0350403 A1
Sheet 2 Grouping visual connections to analyze images more efficiently
How the AI reads a speed limit sign, drawing sheet 3 from US 2026/0350403 A1
Sheet 3 How the AI reads a speed limit sign
Step-by-step image processing stages that classify visual data, drawing sheet 4 from US 2026/0350403 A1
Sheet 4 Step-by-step image processing stages that classify visual data
Software layers that connect an AI app to phone chips, drawing sheet 5 from US 2026/0350403 A1
Sheet 5 Software layers that connect an AI app to phone chips
An AI setup that processes full questions to generate answers, drawing sheet 6 from US 2026/0350403 A1
Sheet 6 An AI setup that processes full questions to generate answers
Feeding text word by word to create a chatbot response, drawing sheet 7 from US 2026/0350403 A1
Sheet 7 Feeding text word by word to create a chatbot response
Typical instructions and user questions sent to a mobile chatbot, drawing sheet 8 from US 2026/0350403 A1
Sheet 8 Typical instructions and user questions sent to a mobile chatbot
Show the other 5 sheets
How an AI tracks back and forth chat history, drawing sheet 9 from US 2026/0350403 A1
Sheet 9 How an AI tracks back and forth chat history
Turning your typed question into an AI response, drawing sheet 10 from US 2026/0350403 A1
Sheet 10 Turning your typed question into an AI response
Splitting the AI to speed up phone replies, drawing sheet 11 from US 2026/0350403 A1
Sheet 11 Splitting the AI to speed up phone replies
Skipping unnecessary steps across multiple chat rounds, drawing sheet 12 from US 2026/0350403 A1
Sheet 12 Skipping unnecessary steps across multiple chat rounds
Steps a phone takes to answer questions faster, drawing sheet 13 from US 2026/0350403 A1
Sheet 13 Steps a phone takes to answer questions faster
Browse all the drawings 13 drawing sheets
Patent filing page

Source. Full patent text and figures from the official USPTO publication PDF.
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