One of the most certain things about the PC industry in 2026 is:More than half of the new computers sold have NPU.But one of the most uncertain things is how many of these NPUs are actually working.
When consulting companies on procurement, we are often asked the same question: "Do you want to change a batch of AI PCs for the company?" The answer depends on which set of data you believe and whether your business needs it.
First look at the data: institutional differences are too big to say the same thing
| organization | Global AI PC Forecast for 2026 | permeability |
|---|---|---|
| Gartner (May 2026) | 143.1 million units | 54.7%(First half broken) |
| Goldman Sachs | 1.5 million units | 59% |
| Counterpoint | "More than half of global shipments" | >50% |
| Canalys | —— | 43.5%(new shipment PC with 40 + TOPS NPU) |
| Morgan Stanley | —— | about 28 per cent(Only 60% in 2028) |
In the same year 2026, optimists say 55% and conservatives say 28%, nearly double the difference.The root cause of differences is different definitions:"Any machine with NPU" is counted as AI PC, and the penetration rate is high; only "Copilot+ PC standard (NPU ≥40 TOPS and AI function is actually enabled)" is counted, and the number is low. Morgan Stan uses the latter strict caliber.
The data of China market is relatively consistent and brighter:
- IDC estimates that in 2026, domestic AI PC shipments will be approximately22 million units, penetration rate 52%, year-on-year growth of 146.5%The compound growth rate for 2025 - 2029 is 58.7%.
- China permeability trajectory of Canalys caliber: 8% in 2023 → 15% in 2024 → 34% in 2025 → 52% in 2026 → 73% in 2028.
- Lenovo 2026 Q1 China AI PC shipped 2.53 million units in a single quarter, accounting for 55% of its PC sales in China.
- In 2025, China shipped 14.62 million AI PCs, with a year-on-year growth rate of more than 150%, more than 140% higher than the overall growth rate of PCs.
There is also a counterintuitive macro context:IDC predicts that overall PC shipments in China will decline slightly year-on-year in 2026But the total market value rose to about $274 billion, an annual increase of 1.6%. That is to say,"shrinking value"-machines sold less, but because of price increases and high allocation, money instead. AI PC is the only structural increment in this pattern.
Hardware threshold: 40 TOPS is admission, but only admission
Microsoft's line for Copilot+ PC isNPU computing power ≥40 TOPS. Actual levels of the three platforms in 2026:
| platform | NPU algorithm | framework | characteristic |
|---|---|---|---|
| Qualcomm Snapdragon X Elite | 45 TOPS | ARM / Oryon | From 2024, the battery life is the strongest, but x86 software compatibility depends on translation. |
| Intel Lunar Lake (Core Ultra 200V) | 48 TOPS | x86 | Energy efficiency and battery life breakthrough, the best office experience |
| Intel Panther Lake (3rd Generation Core Ultra) | NPU5 50 TOPS, platform total 180 TOPS | x86 / Intel 18A | Launched in January 2026, back power supply + surround gate, claiming 27 hours of battery life |
| AMD Strix AI 300 (Strix Point) | 50 TOPS | x86 | Multi-core performance, cost-effective balance |
| Qualcomm Snapdragon X2 Elite | 80 TOPS | ARM | In 2026, thin and light computing power leads the way |
| NVIDIA N1X | 180+ TOPS | ARM / Tensor | Larger-scale models that can be run locally |
| Apple M4 | 38 TOPS | ARM | Stable energy efficiency, but not running Windows, not in Copilot+ range |
In a word:40 TOPS is admission, 80 TOPS is the new flagship, 180+ TOPS can really run a bit of a large model locally.But note that high computing power does not mean that you can use it every day.
What the NPU is doing: what really works and what's eating ash
Sorted by actual usage (industry statistics):
| function | Usage/Description | practical value |
|---|---|---|
| Real-time voice transcription and call summarization | End-side first HF function, 48% adoption rate | Really useful: automatic recording of meetings, real-time subtitles for international calls, low power consumption for NPU execution |
| Photo Editing and Generative Elimination | The second highest frequency, 42% of smartphone users use | Useful but not just needed, PC usage is lower than mobile phone |
| Video Call Studio Effects | Background blur, eye correction, auto framing | Remote office scenarios are practical, NPU execution saves 65-80% more power than GPU |
| Natural Language File Search | 26 H2 New query such as "Zhang sent my quote last week" | Significant value for positions with large document volumes (sales, administration, legal) |
| Local Large Model Reasoning | 7B-8B quantization model on mobile NPU 18.5-28 tokens/sec | The technology is feasible, but it needs 16 - 24 GB of memory + user deployment, and ordinary office users basically do not need it. |
| Copilot Conversation Assistant | Most queries still go to the cloud | NPU participation is low, it is the most virtual part of "AI PC" marketing |
The conclusion was straightforward:At present, the most practical value of NPU is to run voice, image, video and other sensory tasks with low power consumption, so that laptop life becomes better and video conferencing becomes smooth. As for the "local running large model", it is technically feasible, but it is a gray function for most office users.
The real driving force of end-side AI: not showmanship, but three just needed
Why companies are starting to seriously consider local AI? After two years of using the cloud model, the pain point is very clear:
- Data does not go out of the field is a hard red line.Core business documents, confidential R & D data and customer personal information cannot be uploaded to third-party servers. This is a rigid constraint of government and enterprise, manufacturing, financial and medical institutions. It is not "the best", but "must be". Industry statistics show that 76% of IT security leaders require confidential data to be handled locally.
- API long-term cost per token.High-frequency use of the team (customer service, copywriting, code assistance) monthly API costs may be tens of thousands of RMB, three years down the cumulative cost of more than buying a batch of high-equipped machines. Local deployment is a one-time investment.
- Offline and network constrained scenarios.Factory workshop, field, classified intranet, overseas network restricted areas, cloud API is not used at all.
Supporting the industrial conditions are ripe: model lightweight technology (Quantification, distillation and thinning) Make the model with more than ten B parameters reach the practical level in mainstream scenarios such as document processing, code assistance, image generation and data analysis; open source deployment tools are popular, and ordinary technical users can also complete deployment locally; The $38.5 billion edge AI hardware market (Gartner) uses 65 - 80% less GPU power for local execution than for the cloud, and edge filtering of raw data can reduce enterprise cloud bandwidth and export costs by 60 - 85%.
This path is almost identical to the logic of mobile chip performance crossing the threshold before the popularity of smartphones:Mature hardware base + breakthrough in software availability + real demand = scale.
Decision-making framework for corporate procurement: three types of situations
Case 1: Clearly need local AI (buy, buy high)
Trigger conditions (meeting any one of them belongs to this category): compliance requirements for data not to go out of domain; cloud API is already in use and monthly cost exceeds RMB 5000; offline AI capability (field, workshop, classified intranet) is required.
Configuration recommendations:
- NPU ≥50 TOPS (Core Ultra 200V/300, Ryzen AI 300, or Snapdragon X2 Elite 80 TOPS)
- Memory 32GB starting, running native model recommended 64GB--The local 8B model concurrency requires a unified memory baseline of 16-24GB. In addition to system and business software, 32GB is the bottom line.
- SSD 1TB (single model file 4-15GB, multiple models quickly eat up space)
- Note: Memory prices skyrocketed in 2026, and the cost of the 64GB memory configuration has reached RMB 7000. The budget should be compiled according to the actual price.
Case 2: Regular office, no AI (don't pay premium for NPU)
OA, Excel, Kingdee, web pages, email-these jobs do not use NPU at all. This kind of position buys the previous generation of non-AI models (Core Ultra 100 series, Ryzen 7040/8040 series) with the highest cost performance, and the same configuration can save 15-25%.
with one exception: If the machine is going to last more than 3 years, it is safer to choose a new platform with NPU-because Windows 11 has been explicitly bound to NPU (natural language search, Studio Effects, etc.), the old platform will gradually lose support for new features. This is the only reasonable version of "buy new and not buy old" in the AI PC era.
Case 3: The old machine can still run (upgrade first, don't change)
We have done the actual measurement: 8 years ago i5 - 4590 + 4GB memory + mechanical disk, plus 240GB SSD + 8GB memory, boot from 127 seconds to 19 seconds, OA and Kingdee input from card to instant, 32 total cost RMB 12,000 (RMB 380 per capita), compared with the brand-new machine RMB 144,000.Judgment standard: upgrade fee/replacement fee 15%, and expected to last another 3 years, upgrade.<
What machines are not worth upgrading directly: CPU is dual-core low voltage old U, DDR2 platform, motherboard has dark disease, or business has heavily relied on local AI reasoning and large design software-this kind of upgrade cannot solve the calculation generation difference.
Three pit-avoidance reminders for procurement in 2026
- Don't pay a premium for TOPS numbers.50 TOPS and 80 TOPS are no different for office scenarios. They only make sense when running a large local model. Look at your actual needs and don't be led away by the parameter list.
- ARM models (Snapdragon X series) to test software compatibility.The battery life is indeed strong, but x86 software runs by translation, and some industry software (old ERP clients, dongle drivers, specific printer drivers, industrial software) may be incompatible or have degraded performance. You must use real business software for POC testing before purchasing in bulk., don't read the reviews.
- Do not purchase in bulk for the first 3-6 months of new products.The first batch of goods often have BIOS bugs, immature drivers, and unstable supply problems. Enterprises should avoid the first batch of bulk deployment, and wait for the second batch price to loosen and the pit to be trampled before placing an order.
ACCPC provides enterprise PC procurement and bulk PC build services: needs assessment (According to the position classification to the configuration, do not make a one-size-fits-all), brand machine channel procurement (Lenovo/Dell/HP/ASUS, 10 sets from the channel price), complete assembly customization, batch deployment (master production + system cloning + software pre-installation + asset label + ledger), old machine upgrade and recycling, three years on-site warranty. Guangzhou on-site, weekend operations do not stop. Also do Guangzhou computer wholesale and accessories wholesale. Telephone 020-39029800.