Domestic Big Three 2026 H2: Localization Rate Crosses 40% Toward 60%, Ascend 960 Roadmap, MLU690 and S5000 Ecosystems Ramp Up
In 2026, China's AI chip market landscape has shifted from "NVIDIA unipolar dominance" to "overseas vendors leading, domestic multi-route catch-up." According to industry research, China's overall AI accelerator market was ~4M units in 2025, of which 1.65M were domestic, with share first breaking 40%; as products iterate and fabs follow up, the localization rate is expected to rise to 60%-70% by 2027. This article focuses on the latest H2 2026 progress of Huawei Ascend, Cambricon, and Moore Threads — the domestic "Big Three."
1. Huawei Ascend: 950 Capacity Fully Booked, 960 Roadmap Unveiled
Ascend's core advantage is "architecture + full-stack ecosystem synergy," with ~800K units shipped in 2025, capturing 50% of the total domestic vendor share. The product iteration cadence is clear:
| Time | Product | Note |
|---|---|---|
| 2025 Q1 | Ascend 910C | Main transitional model |
| 2026 Q1 | Ascend 950PR | Inference flagship |
| 2026 Q4 (planned) | Ascend 950DT | Training flagship, drives domestic HBM iteration |
| 2027-2028 | Ascend 960 / 970 | Roadmap products |
950 series capacity has entered a "fully booked" state: 950PR entered mass production in April 2026; June monthly capacity jumped to 500K-600K units (nearly 10x MoM), with a full-year target of 1.2M units at 100% certainty; ByteDance locked in 350K units for $5.6B, while Tencent / Alibaba / Baidu combined locked in 400K units.
Ascend 960 roadmap specs (per roadmap disclosure):
| Metric | Ascend 960 |
|---|---|
| Architecture | Ascend 6th gen (Da Vinci v6) |
| FP8 compute | ~4 PFLOPS |
| Memory | 288GB |
| Memory bandwidth | 9.6 TB/s |
| Super-node | Atlas 960 SuperPoD, 15,488 cards, Lingqu optical-electrical converged bus |
| Debut | 2027 Q4 (roadmap) |
The previous-gen Ascend 384 super-node has cumulatively shipped over 750 sets, deployed across 20+ industries including internet, operators, finance, education, and healthcare — Huawei calls it "the only domestic super-node that has trained a SOTA model."
2. Cambricon MLU690: H2 Mass Production, Entering ByteDance Bidding Window
Cambricon is the core domestic compute leader in the absence of an Ascend IPO, with the technology gap continuously narrowing:
- Siyuan 590 (7nm): Performance equivalent to 80% of A100, already supports DeepSeek, continuously adapting to mainstream large models like Qwen 3 and GLM
- Siyuan 690 series: Will enter mass production in H2 2026, expected to achieve order scale-up during ByteDance's H2 bidding window
- Revenue certainty: Equity incentive targets show >100% revenue growth for the next 3 years: 2026 revenue target 13.5B RMB, 2027 27B RMB, 2028 60B RMB
Cambricon fully benefits from the industry dividend of "domestic CSP capex + full adaptation of domestic large models and domestic chips," making it the most direct elasticity play on rising localization rate.
3. Moore Threads MTT S5000: Full-Function GPU + Ecosystem Breakthrough
Moore Threads takes a differentiated "full-function GPU" route, with the flagship MTT S5000 based on the 4th-gen "Pinghu" MUSA architecture:
| Metric | MTT S5000 |
|---|---|
| Dense AI compute | 1000 TFLOPS |
| Memory | 80GB |
| Memory bandwidth | 1.6 TB/s |
| Inter-card interconnect | 784 GB/s |
| Precision | FP8 to FP64 full precision (training + inference) |
| Security | First batch to pass national "Safe and Reliable Evaluation" (Level I) |
Its engineering capability is verified: the Kuae (KUAE) intelligent computing cluster based on S5000 achieves 95% training linear scaling efficiency, with compute efficiency loss within 5% at ten-thousand-card scale; supports checkpoint-resume training with effective training time ratio >90%; and has trained a MoE-236B base model with >25 trillion tokens of corpus from scratch.
The ecosystem is Moore Threads' deepest moat: MUSA has achieved 100% core math library compatibility, 3000+ PyTorch operator compatibility, covers 55 categories of core AI operators, has official vLLM and SGLang support, Day-0 adaptation of mainstream models, and 800K+ developers. Its PD heterogeneous-disaggregation solution achieves equivalent replacement of international high-end GPUs at a 2:1 ratio with S5000, significantly reducing inference cost.
The 5th-gen "Huagang" architecture (released 2025-12) supports FP4 to FP64 full precision, with 50% higher compute density and 10x better energy efficiency than the previous gen, supporting 100K+ card clusters; cumulative R&D investment in the "Huashan" (train-infer integrated) and "Lushan" (graphics rendering) new chips based on this architecture exceeds 900M RMB.
4. Software Ecosystem Decides: Day-0 Adaptation Becomes Routine
Beyond hardware, software ecosystem realization is the watershed for domestic compute in 2026:
- Huawei's CANN heterogeneous computing architecture and MindSeries suite are fully open-sourced, with the community incubating 67 projects, 12.44M+ lines of code, and 3,500+ monthly active developers
- The "release-and-adapt" closed loop between domestic large models and domestic chips has basically formed: Tencent Hunyuan T3 (295B), DeepSeek-V4, and GLM-5.2 all completed Day-0 adaptation
- 2026 is regarded as the "first year of domestic super-nodes"; Huatai Securities estimates China's super-node architecture market will reach 341.4B RMB by 2028, with a 2026-2028 CAGR of 194%
5. Industry Judgment: From "Can It Be Built" to "Can It Be Used Well"
The domestic Big Three are converging along three paths:
- Huawei: Locks government/enterprise and internet big customers with super-node system-level capability + full-stack software
- Cambricon: Impacts the revenue inflection point by narrowing the training-side gap + scaling up via big-customer bidding
- Moore Threads: Covers cloud-edge-end full scenarios with full-function GPU generality + mature CUDA-compatible ecosystem
The common shortcoming of all three remains advanced process and HBM supply — precisely the core link of overseas controls. But as domestic HBM iterates and fabs follow up, a realistic path to 60%-70% localization by 2027 exists.
Related Links
- Huawei Ascend 960 spec page
- Huawei Ascend 950DT spec page
- Cambricon MLU690 spec page
- Moore Threads MTT S5000 spec page
References
- Domestic AI Chip Industry View Update - Robo Datayes
- Moore Threads, Two Positives in One Day - Eastmoney
- Moore Threads × SiliconFlow: PD Disaggregation Heterogeneous Compute Co-location Whitepaper - EE Focus
- After Approaching Break-even, Moore Threads Faces Hong Kong "Big Exam" Again - Top News
This article is compiled from public industry research, broker views, and corporate announcements as of August 2026. Some shipment and market-share figures are third-party estimates, not officially confirmed data.