3 posts tagged with "AI-chip"

June 1-5, 2026, Taipei — Computex 2026 (Taipei International Information Technology Show) wrapped up successfully this week. With the theme "AI Together," industry giants including NVIDIA, Intel, AMD, and Qualcomm unveiled numerous AI compute products in rapid succession. Below, MirrorFrog brings you a roundup of the most noteworthy developments in the compute card space this week.

① NVIDIA DGX Station for Windows: A Desktop AI Supercomputer​

NVIDIA officially launched the DGX Station for Windows during its Computex 2026 keynote, calling it "the world's most powerful desktop AI supercomputer."

Core Specifications​

Item	Specification
Chip	GB300 Grace Blackwell Ultra Desktop Superchip
GPU Memory	252 GB HBM3e (7.1 TB/s)
CPU Memory	496 GB LPDDR5X (396 GB/s)
Unified Memory	748 GB (NVLink-C2C interconnect)
FP4 Compute	20 PFLOPS (sparse)
FP8 Compute	10 PFLOPS (sparse)
Network	ConnectX-8 SuperNIC, up to 800 Gb/s
Model Capacity	Can run 1 trillion parameter models
System Power	1,600 W
Operating System	Microsoft Windows
Shipping	Q4 2026

Significance: DGX Station compresses AI compute power (20 PFLOPS FP4) that previously required datacenter-class clusters into a single desktop workstation. 748GB of unified memory means developers can run models with hundreds of billions or even trillions of parameters locally, without cloud dependency.

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② Intel Crescent Island: Inference-Specialized AI GPU​

At Computex, Intel disclosed detailed specifications for its next-generation datacenter AI inference GPU, Crescent Island.

Item	Specification
Memory	Up to 480 GB LPDDR5x
Power	350 W (PCIe form factor)
Precision Support	FP4/MXFP4 → FP64 (full precision coverage)
Target	AI inference workloads (Agentic Inference)
Positioning	Better price-performance than HBM solutions
Shipping	H2 2026

Significance: Crescent Island represents Intel's key strategic move in the AI inference market. 480GB of massive LPDDR5x memory (non-HBM) means significantly lower cost compared to NVIDIA H200/B200 and other competing products, targeting enterprise inference deployment scenarios.

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③ Intel Xeon 6+ (Clearwater Forest): First Intel 18A Datacenter CPU​

Intel also unveiled the new Xeon 6+ processor, codenamed Clearwater Forest, its first datacenter CPU built on the 18A process:

• 288 Darkmont architecture cores
• L2 288MB + L3 576MB cache
• 12-channel DDR5-8000 memory
• Foveros Direct 3D advanced packaging
• AI Agent Era: CPU returns to the center of infrastructure

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④ NVIDIA RTX Spark Ecosystem Takes Shape​

This week, the RTX Spark super chip developed in collaboration between NVIDIA and MediaTek continued to generate buzz. Multiple OEMs showcased RTX Spark-based laptop and compact desktop prototypes:

• ASUS, Dell, HP, Lenovo, Microsoft Surface, MSI all confirmed as launch partners
• Equipped with 20-core Grace CPU + Blackwell GPU (6144 CUDA cores)
• AI compute 1 PFLOPS
• Retail availability Fall 2026

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⑤ Intel × Foxconn AI Infrastructure Partnership​

Intel and Foxconn announced a joint AI infrastructure initiative, covering the complete chain from chip → server → rack-scale system, targeting the datacenter market opportunity driven by surging AI inference demand.

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⑥ Domestic AI Chip Developments​

According to the IDC 2025 annual report, total AI accelerator card shipments in China reached approximately 4 million units, with domestic vendors shipping approximately 1.65 million units, capturing a market share exceeding 41%. Huawei's Ascend 950 series has entered mass production and delivery, while Cambricon's MLU690 has begun shipping to internet customers.

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This Week's Compute Roundup​

Vendor	Product	Highlight	Timeline
NVIDIA	DGX Station for Windows	20 PFLOPS, 748GB unified memory	Q4 2026
NVIDIA	RTX Spark	1 PFLOPS AI PC chip	Fall 2026
Intel	Crescent Island GPU	480GB LPDDR5x, 350W	H2 2026
Intel	Xeon 6+ (Clearwater Forest)	288 cores, Intel 18A	H2 2026
Intel + Foxconn	AI infrastructure partnership	Chip→rack full chain	Strategic partnership
Huawei	Ascend 950PR/DT	1 PFLOPS FP8, self-developed HBM	In mass production
Cambricon	MLU690	2 PFLOPS FP8, 192GB HBM3E	Shipping

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Sources: NVIDIA GTC Taipei 2026 / Computex 2026 official announcements, Intel press releases, ifeng Tech, IT Home.

June 2026 — Huawei's Ascend 950 series (950PR / 950DT) has entered formal mass production and delivery, a landmark event for China's AI chip industry in 2026. Meanwhile, Cambricon's MLU690 has begun shipping and Moore Threads has announced MTT S5000 specifications, formally establishing China's tri-polar AI chip landscape.

Ascend 950 Series: A Historic Breakthrough with Self-Developed HBM​

Huawei HiSilicon's Ascend 950 series is the fourth-generation Ascend AI chip, first revealed at Huawei Connect 2025 in September and entering mass production in Q1 2026.

950PR (Prefill Inference Specialized)​

Item	Specification
Architecture	Da Vinci v5 (SIMD + SIMT dual-model)
Process	N+2 (SMIC domestic)
HBM	HiBL 1.0 (Huawei self-developed) , 128 GB
FP8 Compute	1 PFLOPS (HiF8 format)
TDP	~400 W
Target	Inference Prefill (video recommendation, real-time interaction)

950DT (Decode + Training Specialized)​

Item	Specification
Architecture	Da Vinci v5 (SIMD + SIMT dual-model)
Process	N+2 (SMIC domestic)
HBM	HiZQ 2.0 (Huawei self-developed) , 144 GB, 4 TB/s
FP8 Compute	1 PFLOPS (HiF8 format)
TDP	~500 W
Target	Inference Decode + Model Training

Historical Significance​

Self-developed HBM (HiBL 1.0 / HiZQ 2.0) represents the most important technical breakthrough of Huawei Ascend 950 — this is the first time a Chinese enterprise has achieved self-developed mass production of HBM memory, completely eliminating dependence on SK Hynix / Samsung HBM supply. Combined with the domestic N+2 process, Ascend 950 has achieved full-chain domestic production from HBM → Compute Die → Packaging → System.

Cambricon MLU690: China's Only Native FP8 Support​

Cambricon's seventh-generation AI chip MLU 690 (Siyuan 690) began volume production and shipping in H1 2026. This is the first domestic AI chip with native FP8 precision support.

Item	MLU 690
Process	5nm (TSMC / SMIC)
FP8 dense	2 PFLOPS
HBM	192GB HBM3E, 5 TB/s
TDP	~500 W
Unit Price (OAM)	~$8,000-12,000

MLU 690's FP8 compute power (2 PFLOPS dense) is on paper comparable to NVIDIA Blackwell (B200 FP8 4.5 PFLOPS sparse). Leveraging its financing advantage as a STAR Market listed company, Cambricon targets 2026 revenue of ¥15-20B (2025: ¥7.2B).

Moore Threads MTT S5000: From Graphics to Training-Inference Unified​

Moore Threads publicly disclosed detailed specifications of the MTT S5000 in February 2026, featuring the fourth-generation MUSA "Pinghu" architecture, single-card AI compute of 1,000 TFLOPS, 80GB GDDR6X memory, 1.6 TB/s bandwidth.

Moore Threads pursues a full-function GPU path (graphics rendering + AI compute + general-purpose compute), closest to NVIDIA's strategy. The founding team comes from former NVIDIA China, and the MUSIFY toolchain helps auto-migrate CUDA code to the MUSA platform, lowering ecosystem migration costs.

China's Tri-Polar AI Chip Landscape​

Dimension	Huawei Ascend	Cambricon	Moore Threads
Core Architecture	Da Vinci v5	MLUv07	MUSA 4th Gen
Process	N+2 domestic	5nm	6nm
FP8 Compute	~1 PFLOPS	2 PFLOPS	0.5 PFLOPS (estimated)
HBM Self-Sufficiency	✅ Self-developed HiBL/HiZQ	❌ Purchased	❌ Purchased
Ecosystem	CANN + MindSpore	NeuWare + MindSpore	MUSA + MUSIFY
Advantage	Full-chain domestic	Highest FP8 compute	Full-function + CUDA migration
2025 Revenue	(Huawei internal)	¥7.2B	¥2.2B

Global Market Comparison (Q2 2026 Update)​

Tier	Vendor	Flagship Chip	FP8/PFLOPS	HBM	Mass Production
Tier 1	NVIDIA	Rubin R200	25 PF (sparse)	288GB HBM4	2026 H2
Tier 2	AMD	MI400	20 PF (dense)	432GB HBM4	2026
	Huawei	Ascend 950DT	1 PF (dense)	144GB self-developed HBM	2026 Q1
	Cambricon	MLU690	2 PF (dense)	192GB HBM3E	2026 H1
	AWS	Trainium 3	5.7 PF (dense)	144GB HBM	2025 Q4 GA
Tier 3	Intel	Gaudi 3	1.8 PF	128GB HBM2e	In production
	Google	TPU v7	4.6 PF(TFLOPS)	192GB HBM	2025
	Moore Threads	MTT S5000	1 PF	80GB GDDR6X	2025 Q1

Note: NVIDIA uses sparse compute as standard, while AMD / Huawei / Cambricon use dense — not directly comparable.

Outlook for H2 2026​

• NVIDIA Rubin R200: Official shipment in H2 2026, 288GB HBM4, 6-chip CoWoS-L packaging
• Huawei Ascend 960: Roadmap H2 2027, expected FP8 compute doubled to 2 PFLOPS
• Cambricon MLU790: Expected 2027, 3nm, 384GB HBM4, 2.5 PFLOPS
• Moore Threads: Next-gen GPU expected with HBM3, 2× MTT S5000 compute

By 2026, China's AI chip industry has formed a complete product matrix from Training (Cambricon MLU690 / Ascend 950DT) → Inference (Ascend 950PR / Moore Threads S5000) → Systems (CloudMatrix / Distributed Clusters).

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This article is based on public information from Huawei Connect 2025 (2025-09-18), industry analysis reports from April 2026, and the latest market data as of June 2026.

June 1, 2026, Taipei — During the Computex 2026 opening keynote, NVIDIA CEO Jensen Huang officially unveiled the RTX Spark super chip, marking NVIDIA's formal entry into the personal computer processor market dominated by Intel, AMD, Qualcomm, and Apple.

RTX Spark: The "Heart" of the Personal AI Computer​

RTX Spark was developed in collaboration between NVIDIA and MediaTek, featuring a heterogeneous package with a 20-core Grace CPU + Blackwell RTX GPU, equipped with 6144 CUDA cores. AI compute reaches 1 PFLOPS (one quadrillion floating-point operations per second), meaning personal computers now possess computing power comparable to a datacenter-class H100 GPU for the first time.

Specification	RTX Spark
CPU	20-core Grace (MediaTek collaboration, Arm architecture)
GPU	Blackwell RTX (6144 CUDA cores)
AI Compute	1 PFLOPS
Target	Personal AI Agent, local LLM inference
Launch OEMs	ASUS, Dell, HP, Lenovo, Microsoft Surface, MSI
Availability	Fall 2026
Form Factor	Laptop SoC + compact desktop workstation

Jensen Huang's "Full-Stack AI" Strategy​

The launch of RTX Spark is a key step in NVIDIA's "full-stack AI" strategy. Jensen Huang stated during the keynote: "AI should not only run in the cloud. Everyone's computer should have the ability to run AI agents."

RTX Spark transforms NVIDIA from a datacenter GPU monopolist into a full competitor in the personal computing market. Following the announcement, shares of AMD, Intel, and Qualcomm fell accordingly.

Market Impact​

• Intel: Personal computer AI processor business faces direct threat
• AMD: Ryzen AI series must compete at the same level
• Qualcomm: Snapdragon X Elite's Copilot+ PC positioning challenged
• Apple: M-series chips are no longer the only high-performance AI PC option

Vera Rubin Platform Enters Full Mass Production​

During the same keynote, Jensen Huang also announced that the NVIDIA Vera Rubin platform has entered full mass production. Rubin R200 features a 6-chip CoWoS-L package (1× Vera CPU + 2× Rubin GPU die + I/O/HBM die), equipped with 288GB HBM4, 22 TB/s bandwidth, and 50 PFLOPS FP4 compute (sparse).

The Rubin NVL72 rack (72 Rubin GPUs + 36 Vera CPUs) will begin shipping in H2 2026.

Other Highlights from Computex 2026​

• AMD: Showcased the MI350 series (192GB HBM3e, 5 PFLOPS FP8 dense), officially launching in June
• Intel: Jaguar Shores publicly unveiled for the first time
• Qualcomm: AI 200 / 300 series inference card roadmap updated
• Domestic AI Chip Zone: Huawei, Cambricon, Moore Threads, and others showcased their latest products

Industry Significance​

The launch of RTX Spark means AI compute is no longer confined to datacenters. Individual developers, designers, and researchers will be able to run large model tasks locally that previously required cloud GPUs, potentially redefining the market landscape for personal AI computing.

The mass production of Vera Rubin further consolidates NVIDIA's absolute leadership in datacenter AI training. Together, both product lines form NVIDIA's full-stack AI computing landscape of "cloud training + personal inference."

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This report is based on official NVIDIA announcements from Computex 2026 / GTC Taipei on June 1, 2026.