The Tool Desk
Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Huawei’s Ren Zhengfei said in remarks reported by Network World on June 10, 2025, that the company remained a generation behind U.S. rivals in chip performance. Huawei is trying to narrow that gap by linking chips into large systems and developing new processors, interconnects and software. Its announcements show an active roadmap, not proof of parity: the available sources do not establish an independent, apples-to-apples comparison of current Huawei and Nvidia chips and systems.
What Ren Zhengfei meant by “a generation behind”
Network World’s June 10, 2025 report described Ren’s assessment as a gap in chip performance. It also reported that he pointed to cluster computing, mathematical methods and approaches beyond conventional Moore’s Law scaling as ways to compensate for weaker individual chips. This is a reported characterization from 2025, not a benchmark of Huawei’s products today.
“The gap” can mean several different things: how fast one chip performs a particular workload, how much useful work a full system can deliver, how many chips a company can supply, or how efficiently it can run a workload. A comparison can differ across those measures. The reviewed sources do not provide a controlled, independent test that settles them all.
How Huawei is trying to narrow the gap
Combining chips into larger systems
Huawei’s September 2025 roadmap described the Atlas 900 A3 SuperPoD as containing up to 384 Ascend 910C chips. Huawei said at the time that more than 300 of those systems had been deployed to more than 20 customers. These are company-reported specifications and deployment figures; they describe system scale, not independent proof that each chip matches a U.S. rival.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
#1 Best Overall
In a September 17, 2026 keynote, Huawei described the Atlas 960E SuperPoD and its Hi-ONE optical interconnect, and reported that more than 1,000 Atlas 900 A3 SuperPoDs had been deployed. It also said Atlas 950 was seeing large-scale commercial use. Those deployment statements, too, are Huawei’s own figures. A large cluster can improve total system capability, but it does not change the performance of an individual processor.
Developing the Ascend roadmap
Huawei’s September 2025 announcement outlined Ascend 950, 950DT, 960 and 970 plans. Its September 2026 keynote updated the schedule for two products: Huawei said Ascend 960DT would be available in the first quarter of 2027 and 960PR in the third quarter of 2027, earlier than its previous schedule. These are company-announced availability targets, not confirmation of shipping volumes or independently measured performance.
Investing in research and software
Network World reported that Ren cited annual R&D investment of $25 billion (180 billion yuan) in 2025. Separately, Huawei’s 2025 Annual Report put company-reported R&D spending at CNY192.3 billion, or 21.8% of revenue. These figures come from different reporting contexts and should not be treated as a like-for-like measurement. Spending can support chip design and software development, but it does not by itself establish manufacturing capacity or competitive performance.
Huawei’s 2026 keynote also emphasized its broader ecosystem. Software support, developer tools and portability can affect how useful a system is for a particular AI workload; the company’s ecosystem statements are not independent evaluations of compatibility or performance.
Rank #2
- 8K30fps 360° Video with Dual 1/1.28" Sensors: Capture stunning detail with dual 1/1.28" sensors shooting up to 8K30fps. Film epic adventures, everyday moments, and more, all in sharp, immersive 360° video with better clarity, color, and dynamic range
- Triple AI Chip Design, Better Low Light: Shoot confidently even in challenging lighting. X5’s triple AI chip design powers advanced noise reduction and image processing, delivering crisp, vibrant footage even in dim or night conditions
- Invisible Selfie Stick: Create impossible third-person views with no selfie stick in sight! Capture everything in 360°, then choose your angles later using AI-assisted reframing—perfect shots, every time
- InstaFrame Mode: Get a ready-to-share flat video instantly. Choose auto-framing to let the camera track you, or lock in a fixed angle. Preview the 360° video later to add in any unexpected moments, too
- FlowState Stabilization + 360° Horizon Lock: No gimbal needed. X5’s FlowState Stabilization and full 360° Horizon Lock deliver buttery-smooth, level footage, even during action-packed moments, bumps, or full rotations
What the available performance comparisons do—and don’t—show
The U.S. House Select Committee on the CCP’s 2025 report said Nvidia’s Blackwell B100, GB200 and GB300 products had roughly two, three and four times the performance of the Ascend 910C, respectively. Those are the committee report’s comparisons, not results from a controlled benchmark presented in the reviewed material. They should not be generalized to every workload, configuration or Huawei chip.
System performance also depends on more than a processor’s headline capability. Memory, interconnect, software support, power use and the workload itself can change the result. Network World noted that Huawei’s cluster strategy may require more power, but the reviewed sources do not provide an equivalent full-system test that quantifies an efficiency gap.
- Single-chip performance: compare a specified chip on a specified workload and precision; the committee report’s 910C comparison is one attributed estimate, not a universal ranking.
- System capability: account for the number of chips, memory and interconnect, as well as measured workload results. Huawei’s SuperPoD descriptions are company claims.
- Aggregate compute: depends on both usable performance and how many chips can be produced and deployed.
- Efficiency and software: require workload-matched evidence; the reviewed sources do not establish an apples-to-apples comparison across these dimensions.
Why estimates of Huawei chip output differ
Published estimates of Huawei’s 2025 Ascend output vary sharply. The House Select Committee report compiled three figures with different origins. The Council on Foreign Relations (CFR) also modeled an aggressive scenario using 800,000 chips. None of these sources supplies an audited final production count.
| Figure | What it represents | Attribution and qualification |
|---|---|---|
| No more than 200,000 | Ascend AI chips made indigenously in 2025 | A U.S. government assessment cited by the U.S. House Select Committee on the CCP in its 2025 report; an assessment, not an audited final count. |
| 250,000 | Equivalent Ascend 910Cs | A press estimate cited by the committee’s 2025 report; not an audited final count. |
| As many as 800,000 | Ascend 910Cs | A higher analysis cited by the committee’s 2025 report, which said a stockpile of high-bandwidth-memory wafers could help enable that level. CFR also used 800,000 as an aggressive production assumption in its 2025 analysis. Neither source establishes that this output was achieved. |
| Over 14 million | AI chips projected to be produced and deployed in the United States in 2025 | A projection cited by the committee’s 2025 report, not a verified final count or a direct measure of comparable compute. |
The figures are not interchangeable: some refer to indigenous Huawei chip manufacturing, one is a press estimate of equivalent 910Cs, and another is a projection for U.S. AI-chip production and deployment. Chip counts also do not account for differences in usable performance, configuration or availability.
CFR’s 2025 analysis modeled different production assumptions and argued that Huawei’s aggregate AI compute would remain a small fraction of Nvidia’s in both its median and aggressive scenarios. Those are scenario forecasts, not observed output or a final measurement. The disagreement over production estimates is one reason not to infer that Huawei has matched its rivals from a single headline number.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What still constrains Huawei—and what can be concluded
The House Select Committee report and CFR analysis identify access to advanced manufacturing equipment and the limits of domestic foundry capability as constraints on Huawei’s ability to make advanced chips at quality and scale. The committee’s higher 910C estimate also illustrates how assumptions about available memory supplies can affect an output projection. These constraints matter to manufacturing volume and aggregate computing capacity; they do not mean every Huawei chip or workload has an identical performance gap.
The strongest supported conclusion is that Huawei is building a broader AI-computing platform and has announced increasingly ambitious chips, SuperPoDs and interconnects. Its own deployment claims indicate that it says these systems are reaching customers. But roadmap targets and company-reported deployments do not demonstrate that Huawei has caught up in per-chip performance, efficiency, software support, manufacturing scale or aggregate compute. The answer depends on which of those measures matters, and the available sources do not provide a single independent test that resolves them.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problems
