Skip to main content

One post tagged with "monthly-roundup"

View all tags

June 2026 AI Chip Major Events Roundup: Ascend 910C Trains Trillion-Parameter Model, OpenAI Custom Chip, RTX Spark Launch

· 6 min read
AI Compute Cards Wiki Editorial
Industry Research Team

June 2026 saw multiple milestone events in the AI chip field, marking acceleration of two major trends: "domestic substitution" and "de-NVIDIA-ization."

1. Huawei Ascend 910C Completes 1.6-Trillion-Parameter DeepSeek V4 Pro Training (2026-06-05)​

Event Overview​

June 5, 2026, Shenzhen Hetao College, together with Harbin Institute of Technology (Shenzhen), Shenzhen Big Data Research Institute, Huawei, and other teams, relied on an Ascend 910C domestic AI compute cluster to successfully complete full-parameter post-training of the 1.6-trillion-parameter DeepSeek V4 Pro large model.

Technical Significance​

MetricValue
Model parameters1.6 trillion
Training chipAscend 910C cluster
Training typeFull Parameter Post-Training
SignificanceFirst time domestic AI chips complete trillion-parameter-level model training

Industry Impact​

  1. Breaks technology blockade: Proves domestic AI chips can train trillion-parameter models
  2. Accelerates "farewell to NVIDIA": DeepSeek fully switches to Huawei Ascend, reducing dependence on H100
  3. Domestic substitution inflection point: From "inference substitution" to "training substitution"

2. OpenAI Launches First Custom AI Inference Chip Jalapeño (2026-06-24)​

Event Overview​

June 24, 2026, OpenAI and Broadcom jointly launched the first custom AI inference chip Jalapeño, with a design cycle of only 9 months (industry average 18 months), using TSMC 3nm process.

Key Metrics​

MetricJalapeñoComparison (Blackwell)
ProcessTSMC 3nmTSMC 4nm
ArchitectureSystolic ArrayBlackwell GPU
Design cycle9 months~18 months
Inference cost-50%Baseline
AI-assisted design✅ First❌ No
DeploymentEnd of 2026Shipped

Strategic Significance​

  1. First AI chip with AI-assisted design: OpenAI used models like GPT-5.3-Codex-Spark to assist architecture exploration
  2. Accelerates "de-NVIDIA-ization": Tech giants (Google, Amazon, Microsoft, Meta, OpenAI) collectively develop custom chips
  3. Inference cost revolution: For OpenAI processing hundreds of millions of API calls daily, a 50% cost reduction is significant

3. NVIDIA Launches RTX Spark AI PC Superchip at Computex 2026 (2026-06-01)​

Event Overview​

June 1, 2026, NVIDIA CEO Jensen Huang launched the RTX Spark AI PC superchip at Computex 2026 / GTC Taipei, in collaboration with MediaTek, using an Arm CPU + Blackwell GPU unified-memory architecture.

Key Metrics​

MetricRTX Spark
CPUUp to 20-core Arm (with MediaTek)
GPU6,144 CUDA cores (Blackwell)
Unified memory128GB LPDDR5X (shared CPU+GPU)
Memory bandwidth300 GB/s
AI compute~1 PFLOPS (est.)
Model capacityCan run 120B-parameter models
ContextUp to 1 million tokens
TDP~100W (est.)
AvailabilityFall 2026

Industry Impact​

  1. NVIDIA enters PC chip market: Challenges Intel's dominance in personal computers
  2. New AI PC standard: Run 120B-parameter models locally, 1M-token context
  3. Windows transforms into AI Agent platform: Deep collaboration with Microsoft OpenShell framework

4. MIIT Publishes "2026 AI Chip Industry Development White Paper" (2026-06-09)​

Event Overview​

June 9, 2026, China's Ministry of Industry and Information Technology published the "2026 AI Chip Industry Development White Paper," predicting the domestic AI chip market will exceed 200 billion RMB in 2026.

Key Predictions​

Metric2026 Prediction
Market sizeExceed 200 billion RMB
Domestic chip share>50% (41% in 2025)
Edge inference chipsSignificant progress
Shipment growthMore than double (vs 2025)

Industry Significance​

  1. Domestic AI chip capitalization accelerates: Cambricon, Enflame, Moore Threads, etc. accelerate IPOs
  2. Edge inference becomes the breakthrough: Easier to achieve domestic substitution than training chips
  3. Policy dividend continues: Domestic substitution upgraded from "market behavior" to "national strategy"

5. ByteDance in Talks to Procure 50K Iluvatar Inference Chips (2026-06-17)​

Event Overview​

June 17, 2026, Reuters reported that ByteDance is in talks with Shanghai AI chip firm Iluvatar to procure at least 50,000 AI chips, mainly for inference tasks.

Deal Details​

ItemContent
BuyerByteDance
SupplierIluvatar
Chip modelZhiKai series (inference GPU)
QuantityAt least 50,000
UseInference workloads
Training chipTianTai series

Industry Significance​

  1. Domestic GPU top player "adds a member": Iluvatar enters a top internet company's supply chain for the first time
  2. ByteDance 2026 capex raised over 200B RMB: Mainly for AI compute and datacenters
  3. "Domestic substitution" extends from government/SOEs to private tech giants

Trend 1: "Domestic Substitution" Moves from Inference to Training​

  • Ascend 910C completes 1.6-trillion-parameter model training → Proves domestic chips have training capability
  • DeepSeek fully switches to Ascend → Leading AI companies first to "farewell to NVIDIA"
  • ByteDance procures Iluvatar → Private tech giants follow

Trend 2: "De-NVIDIA-ization" from Slogan to Action​

  • OpenAI Jalapeño → First custom chip, inference cost -50%
  • Google TPU, Amazon Trainium, Microsoft Maia → Continuous iteration
  • Meta MTIA, Apple M5 Ultra → Increased investment

Trend 3: AI PC and Edge Inference Become New Battlefield​

  • NVIDIA RTX Spark → New AI PC standard, launches Fall 2026
  • Edge inference chip localization accelerates → Key mention in MIIT white paper
  • "Local trillion-parameter model execution" → New consumer market selling point

Looking Ahead (2026 H2)​

  1. Ascend 950DT full scale-up (2026 Q4) → Huawei's latest-gen training chip
  2. NVIDIA Rubin R200 shipment (2026 H2) → Next-gen flagship
  3. AMD MI400 Helios rack (2026 H2) → Targets NVIDIA GB200
  4. OpenAI Jalapeño deployment (end of 2026) → Gigawatt-scale datacenters
  5. Domestic AI chip shipments more than double → CITIC Securities prediction

References​

This article is continuously updated. Please provide the latest developments.