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How Huawei and DeepSeek Are Building an Alternative to Nvidia’s AI Ecosystem
Huawei brings Ascend hardware and native software; DeepSeek brings models, workloads and engineering.
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Key takeaways
- Huawei brings Ascend hardware and native software; DeepSeek brings models, workloads and engineering.
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openai.comCreate a landscape editorial hero image for this Studio Global article: What does Bryan Shan and Dylan Patel’s October 21 SemiAnalysis report, “The Huawei-DeepSeek Symbiosis,” reveal about how Huawei’s hardware a. Article summary: The report’s central argument is that Huawei and DeepSeek together can narrow Nvidia’s ecosystem lead: Huawei supplies hardware and native software, while DeepSeek supplies demanding AI workloads and engineering that mak. Topic tags: general, general web, user generated. Style: premium digital editorial illustration, source-backed research mood, clean composition, high detail, modern web publication hero. Use reference image context only for broad subject, composition, and topical grounding; do not copy the exact image. Avoid: logos, brand marks, copyrighted characters, real person likenesses, fake screenshots, UI text, readable text, watermarks, charts with fa
Huawei can supply chips and a native software stack, but it needs demanding AI workloads and engineering to show what that platform can do. DeepSeek needs computing capacity and a platform it can optimize for its models. That mutual dependence is the central point of SemiAnalysis’s report: the partnership could help narrow Nvidia’s ecosystem advantage, but the evidence does not show that Huawei has erased the performance gap.1
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Why the partnership is complementary
SemiAnalysis frames the relationship as one neither company can build alone. Huawei has its own Pangu models, but the report says it lacks a frontier AI lab to prove its chips in training and inference. DeepSeek has models and engineering expertise, but needs compute. Huawei contributes hardware and native software; DeepSeek contributes workloads and engineering that can make the platform more useful.1
That distinction matters. A chip’s specifications alone do not make it a competitive AI platform. Software support and the ability to run real workloads are also part of the equation. The report’s thesis is that DeepSeek can help Huawei strengthen those parts of its ecosystem, while Huawei can offer DeepSeek another source of compute.1
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Ascend support expands the software effort
A roundup of the SemiAnalysis report says DeepSeek added Ascend support to six projects: TileLang, DeepGEMM, DeepEP, TileKernels, FlashMLA and DeepSelect. The same summary notes that, at the time of writing, only TileLang was usable because CANN 9.2.0 had not yet been released.7 That caveat makes the software work evidence of an ongoing effort—not proof that every component was ready for broad use.
The available source material does not establish that all six projects were originally Nvidia-focused. The more supportable takeaway is that DeepSeek was extending Ascend compatibility across a collection of AI software tools.7
What the Ascend 950PR benchmark does—and does not—show
A secondary digest summarizing the report says Huawei’s Ascend 950PR kernels reached 99.7% of the theoretical ceiling on BF16 matrix-math tests. It also places the chip’s overall performance between Nvidia’s A100 and AMD’s MI300X.6
These are different kinds of comparisons. Reaching a high share of a chip’s theoretical ceiling indicates that a kernel can use that hardware efficiently for a particular operation. It does not establish that the chip matches a faster competitor in absolute performance, or that it performs as well across different workloads. The reported 99.7% figure is therefore notable, but it is not evidence of Nvidia parity.6
The supplied source material does not verify the claimed memory-bound efficiency comparison with the H100 or the reported limits on running certain optimizations on x86 servers. Those details should not be treated as established from the available evidence.
A possible shift, not a completed migration
The South China Morning Post reports SemiAnalysis’s forecast that DeepSeek may rely primarily on Huawei’s technology stack by 2027 or 2028. That is a prediction about a possible future direction, not confirmation that DeepSeek has already moved its workloads or that the transition is certain.2
The report’s argument is best understood as an ecosystem story: Huawei has hardware and native software; DeepSeek can bring models, workloads and engineering that test and improve the platform. The benchmark summary suggests Huawei can use its hardware efficiently on at least some matrix-math tests, while the software rollout points to a broader compatibility effort. Neither establishes that Huawei has caught Nvidia across overall performance or ecosystem maturity.1
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Huawei brings Ascend hardware and native software; DeepSeek brings models, workloads and engineering.