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AI News

Guo Mingzhan: Apple AI Chip Mass Production Is Imminent, to Be Used in Self-built Data Centers in 2027

Apple plans to mass-produce its self-developed server AI chips in late 2026 and launch new data centers equipped with them by 2027 to meet growing on-device AI demand, while accelerating AI infrastructure investments, including building an AI server factory in Houston.....

6.2k 4 hours ago

Guo Mingzhan: Apple AI Chip Mass Production Is Imminent, to Be Used in Self-built Data Centers in 2027

Zuckerberg Announces Meta Compute Initiative: Heavy Investment in Self-Built AI Energy and Computing Infrastructure

Meta launches 'Meta Compute' to build large-scale computing and power facilities, aiming to lead in AI competition. Zuckerberg targets tens of gigawatts by 2030, scaling to hundreds long-term to meet AI investment commitments.....

9.5k 6 hours ago

Musk's xAI Plans to Invest Over $20 Billion in Mississippi to Build Data Centers

Elon Musk's xAI plans to invest over $20 billion in a Mississippi data center to meet rising computing demands from generative AI, highlighting tech giants' infrastructure investments for AI competitiveness.....

9.9k 34 minutes ago

Musk's xAI Plans to Invest Over $20 Billion in Mississippi to Build Data Centers

Microsoft's Latest Report: DeepSeek Becomes a Dark Horse with High Cost-Effectiveness, Gaining Over 50% Market Share in Some Overseas Regions

DeepSeek, a Chinese AI firm, gains market edge in developing nations with cost-effectiveness, helping bridge the global digital divide. Microsoft reports 16.3% generative AI user penetration, yet infrastructure and investment gaps persist between developed and developing countries.....

9.8k 6 hours ago

AI Products

MTIA

Meta Training and Inference Accelerator (MTIA) is Meta's self-developed next-generation AI training and inference acceleration chip. Compared to the previous generation, MTIA v2 has significantly improved computing power and memory bandwidth, enabling more efficient support for Meta's sorting and recommendation model applications. This is a significant achievement in Meta's continuous investment in self-developed hardware infrastructure, which will bring new capabilities to Meta's AI products and services.

Hardware infrastructure

6.6k

Models

Claude Opus 4.1

Anthropic

$105

Input tokens/M

$525

Output tokens/M

200

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GLM-4.5-AirX

Chatglm

Input tokens/M

Output tokens/M

128

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GLM-4.5-Air

Chatglm

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Output tokens/M

128

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Gemma 3n E2B Instructed

Google

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Pangu-MM-M2-AIGVideo-1.0.0

Huawei

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GLM-Z1-Air

Chatglm

Input tokens/M

Output tokens/M

128

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GLM-Z1-AirX

Chatglm

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Output tokens/M

128

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Yi-Lightning

01-ai

$0.99

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$0.99

Output tokens/M

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Gemma 2 9B

Google

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Yi-Medium

01-ai

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Yi-Large-Turbo

01-ai

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Yi-Large

01-ai

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Yi-Large-RAG

01-ai

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Yi-9B-200K

01-ai

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Output tokens/M

200

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Yi-9B

01-ai

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Yi-6B-Chat

01-ai

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Yi-34B-Chat

01-ai

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Yi-6B-200K

01-ai

Input tokens/M

Output tokens/M

200

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Yi-34B-200K

01-ai

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Output tokens/M

200

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Yi-34B

01-ai

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