Free tools Windows power users keep installed
One-click scans. No signup required.
iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Not conclusively. Huawei’s chairman said he believed Ascend’s share of China’s AI-chip market should exceed Nvidia’s, but Huawei supplied no supporting data, and he acknowledged that reliable figures for Nvidia’s share are difficult to obtain. Separate analyst estimates suggest a dramatic shift, but they are estimates and a forecast—not an audited market tally.
What do the market-share estimates actually say?
The available figures point to Huawei gaining ground in China, but they do not establish a definitive winner. The Associated Press reported Bernstein estimates that Nvidia and Huawei each had about 40% of China’s AI-chip market in 2025, followed by a forecast for 2026 that puts Huawei at about 50% and Nvidia at around 8%.
| Period | Nvidia | Huawei | How to read it |
|---|---|---|---|
| 2025 | About 40% | About 40% | Bernstein estimates, as reported by the Associated Press in 2026; not an audited market-share count. Associated Press |
| 2026 | Around 8% | About 50% | Bernstein forecast reported by the Associated Press in 2026; it is a projection, not a final result. Associated Press |
Huawei rotating chairman Eric Xu offered a separate, less quantified view on September 17, 2026: “I think Ascend market share should be bigger than Nvidia’s.” Reuters reported that Xu also said reliable data on Nvidia’s China share were hard to obtain and that Huawei provided no figures to support his belief. The company’s assertion and Bernstein’s estimates should therefore be treated as distinct claims, not combined into a confirmed market result. Reuters via Investing.com
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Does a bigger share mean Ascend has replaced Nvidia?
No. Market share is not a measure of whether one accelerator is faster for every task or whether one vendor has displaced the other across all AI workloads. The Associated Press reported that Nvidia continues to matter to Chinese AI development and that Huawei’s high-performance chips lag Nvidia’s most advanced products in many areas. A falling share estimate for Nvidia in China would not, by itself, prove that Nvidia has lost technical relevance or that Ascend can substitute in every deployment. Associated Press
#1 Best Overall
- NVIDIA Volta GV100 Architecture — 4,608 CUDA Cores, 640 1st-Gen Tensor Cores delivering 14 TFLOPS FP32 and 112 TFLOPS deep learning performance for AI training, inference, HPC, and scientific computing workloads
- 32GB HBM2 ECC Memory — 900 GB/s Bandwidth — High-bandwidth memory on a 4096-bit bus with ECC error correction provides the memory capacity and throughput required for the largest AI models, simulations, and datasets
- PCIe 3.0 x16 Interface — 250W TDP — Standard PCIe Gen3 connectivity with passive cooling designed for enterprise rack server deployment in HPE ProLiant, Dell PowerEdge, and Supermicro platforms with adequate chassis airflow
- NVLink — Scale to 96GB Unified Memory — Connect two V100 GPUs via NVLink at 300 GB/s bi-directional bandwidth to scale GPU memory from 32GB to 96GB for larger AI training and HPC workloads
- Multi-Precision Computing — Supports FP64 (7 TFLOPS), FP32 (14 TFLOPS), FP16 (112 TFLOPS) and INT8 precision modes for flexible deployment across training, inference, and scientific simulation workloads
Why is Huawei building chips and systems of its own?
The immediate strategic reason is supply control. Huawei is trying to build an AI-computing stack it can develop and supply without relying on American chip technology. Xu said Huawei could not produce enough AI computing equipment to meet demand in China and was limiting overseas sales. He put the motivation plainly: “We cannot accept a destiny where we cannot control our fate being determined by others in terms of willingness to sell chips to China or not.” Reuters via Investing.com
That effort is not just about making an individual processor. Large AI deployments depend on connecting accelerators into systems and giving developers software tools to use them. Huawei’s push combines Ascend chips, connected computing systems and software support—a broader contest with Nvidia’s hardware and its established CUDA developer ecosystem.
How do Ascend and Nvidia compare in practice?
A useful comparison has to distinguish workload, generation and the complete system rather than rely on one performance figure. The available reporting does not provide an independent, apples-to-apples benchmark for Ascend 950DT against a current Nvidia accelerator.
Rank #2
- Powered by Radeon AI PRO R9700 - Supercharge you workflow with the cutting-edge RDNA 4 Architecture and 2nd-gen AI Accelerators.
- 32GB GDDR6 with 256-bit memory bus - Tackle larger, more complex projects without limits.
- PCIe Gen 5 - Unlock lightning-fast data transfers with PCIe Gen 5 support.
- GIGABYTE TURBO Fan Cooling System - Indented metal cover and blower fan increase airflow intake, while the vapor chamber, all copper heat sink, and metal frame offer efficient heat dissipation. Optimized airflow design allows for easy multi-GPU scalability.
- Double Ball Bearing Fan - Delivers superior heat resistance and rotational efficiency for better performance and a longer lifespan compared to conventional sleeve fans.
Training and inference are different tests
Reuters reported that Huawei’s Ascend 950DT card integrates an AI processor with memory and other components and is aimed primarily at developing models and generating responses. The 950PR is described as handling user requests before they reach the model. These are different roles in a computing system, so their capabilities should not be collapsed into a single chip-versus-chip claim. Reuters via Investing.com
Gregory C. Allen’s April 2025 testimony to the U.S. House Committee summarized a reported comparison in which Ascend 910C achieved roughly 60% of Nvidia H100 performance for inference. That is a historical, reported comparison for a specific chip and workload—not an independent benchmark, not a training result, and not evidence of 950DT performance. U.S. House Committee testimony
Whole systems and software matter
Connecting many processors efficiently, moving data between them and giving developers familiar tools can be as important to deployment as the performance of a single chip. Nvidia’s CUDA ecosystem remains an advantage because developers have built substantial software and workflows around it. Huawei is working to reduce that gap, but ecosystem activity is not proof that the gap has closed.
Rank #3
- [Local AI Inference & 70B Model Ready] Equipped with the AMD Ryzen 7 PRO 8845HS processor, NEXUS is engineered for heavy local AI workloads. With a full-size GPU bay, it runs 70B LLMs natively without an internet connection. Ideal for AI developers and tech enthusiasts who need private environment for coding and model testing.
- [132TB Mass Storage with ZFS Integrity] Features a hybrid storage architecture (3×NVMe + 4×3.5" HDD) supporting up to 132TB. Utilizing the enterprise-grade ZFS file system and ECC memory, it prevents data corruption and bit rot—a must-have for professional photographers and video editors safeguarding 4K/8K RAW footage.
- [OpenClaw-Driven Automation Workflow] The built-in OpenClaw execution layer allows complex automated tasks to be processed locally. Even when offline, your backup schedules and AI file organization continue seamlessly. Say goodbye to monthly cloud subscriptions and high latency.
- [Dual 10GbE & USB4 Ultra-Connectivity] Experience server-class speeds with dual 10GbE ports and a 40Gbps USB4 interface. It enables multi-user real-time collaboration on large project files directly from the NAS, ensuring zero-lag editing for creative studios and production teams.
- [Open-Source ZimaOS for Total Privacy] Running on the fully open-source ZimaOS, NEXUS ensures your data stays physically on-premise with no backdoors. It acts as a "Digital Fortress" for privacy-conscious families and small businesses who demand absolute data sovereignty.
On October 1, 2026, reporting on a DeepSeek–Huawei collaboration described programming tools for Ascend that include compute and chip-to-chip communication libraries, along with TileLang support. The tools address both work within an accelerator and communication between accelerators. Tom’s Hardware
Supply and memory can limit what gets deployed
Reuters reported that high-bandwidth memory (HBM) scarcity and cost were affecting Chinese AI-chip makers. It also reported that the indicated price for an Ascend 950DT exceeded 250,000 yuan (US$37,255), based on information from two people familiar with pricing discussions. That is not a published Huawei price list or an official retail quote. Reuters via Investing.com
These constraints help explain why a market-share forecast should not be read as a simple measure of chip quality. Availability, memory supply, system capacity, workload fit and software support all affect which accelerators organizations can actually use.
Rank #4
- Professional AI & Creator Workstation: AMD Radeon AI PRO R9700 GPU with 32GB GDDR6 is engineered for AI development, professional content creation, and compute-intensive workloads.
- Massive 32GB Memory Capacity: 32GB of GDDR6 memory on a 256-bit bus provides ample bandwidth for large AI models, 8K video editing, and complex 3D rendering.
- Advanced RDNA 4 with AI Accelerators: 64 Compute Units with 3rd Gen Ray Tracing and dedicated 2nd Gen AI Accelerators for groundbreaking AI performance and visual computing.
- Professional Blower Cooling: Efficient single blower design exhausts heat directly out of the chassis, ideal for multi-GPU workstation and server configurations.
- Enterprise-Grade Thermal Solution: Vapor chamber heatsink with industrial Honeywell PTM7950 thermal interface material ensures reliable cooling under sustained professional loads.
How far has Huawei’s software ecosystem progressed?
Huawei is building out CANN, its software stack for Ascend, and says it is moving toward sustained, community-driven open-source development. In a September 2026 company account, Huawei said Ascend supported more than 90 leading third-party open-source projects. Huawei also reported more than 5,200 monthly active developers and over 40 AI models pre-trained on its stack; Reuters separately reported Huawei’s claims that more than 5,200 developers were active monthly and over 40 models had been trained directly on its computing platform. These are company-reported adoption measures, not independently audited counts. Huawei Reuters via Investing.com
Huawei executive David Wang said the company was evolving Ascend on a “one-generation-a-year cycle.” Huawei also said testing of the 950DT had produced good results and expected model developers to begin training on systems using it the following year. Reuters reported the chip was expected in the fourth quarter of 2026. These are company statements and plans, not independent test results or confirmation of completed deployment. Huawei Reuters via Investing.com
Quick wins for a faster PC:
Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →What is the clearest conclusion for AI buyers and developers?
Huawei is becoming a more important domestic alternative in China, and Bernstein’s reported forecast suggests its share could grow substantially. But the forecast is not a final market count, Huawei’s own share claim is unsupported by published company data, and the evidence does not show that Ascend has displaced Nvidia across workloads. For a real deployment decision, compare the specific accelerator generation and workload, the full system and interconnect, software compatibility, memory and supply availability, and the price actually offered—not just a national market-share estimate.
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.
