#1.6 trillion parameters
30 related articles
·2 分钟
DeepSeek V4 Official Release Imminent: What 1.6 Trillion Parameters Really Means
DeepSeek V4 official release is imminent. V4 Pro features 1.6 trillion parameters with million-character context. Explore the D-SPARK acceleration framework, dynamic pricing, and V4's leap to production-grade AI.
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·3 分钟
Is LLM Inference Actually Profitable? Breaking Down the Cost Structure and Business Logic of Large Model Inference
A deep dive into LLM inference cost structure and profitability models—from GPU throughput, MoE architecture, and KV Cache to scale effects—revealing the business logic behind API price wars.
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·4 分钟
What Is the True Nature of Large Language Models? A Super Compressor Analogy to Help You Fully Understand
Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.
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·4 分钟
What Is the True Nature of Large Language Models? A Super Compressor Analogy That Makes Everything Click
LLMs aren't search engines — they're more like super compressors. This article explains how large models compress corpora to learn semantic patterns, and explores the principles and limitations of emergent intelligence.
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·2 分钟
DeepSeek V4 Coming Soon, Meituan Open-Sources 1.6 Trillion Parameter LongCat 2.0
DeepSeek V4 launches mid-July with peak/off-peak pricing; Meituan open-sources trillion-parameter MoE model LongCat 2.0 with million-token context; Cursor debuts iOS app. A quick look at the latest AI industry news.
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·2 分钟
DeepSeek V4 Coming Soon; Meituan Open-Sources 1.6-Trillion-Parameter LongCat 2.0
DeepSeek V4 official release expected mid-July with peak/off-peak pricing; Meituan open-sources trillion-parameter MoE model LongCat 2.0 with million-token context; Cursor launches iOS app. A quick look at the latest AI industry news.
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·3 分钟
How China's Open-Source LLMs Are Closing In on America's Closed-Source Giants
Kimi, Alibaba Qwen, and DeepSeek leverage MoE architecture, home-field data advantages, and the open-source flywheel to close in on OpenAI and Anthropic at ultra-low cost. A deep dive into China's open-source LLM catch-up.
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·6 分钟
How the Creator of Redis Squeezed a 284-Billion-Parameter DeepSeek Into an Ordinary Laptop
Redis author antirez built the pure-C inference engine DS4 "Dwarf Star," compressing DeepSeek V4 Flash from 500GB to 80.8GB via asymmetric quantization for local deployment on 128GB unified memory at 26.7 tokens/sec.
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·6 分钟
How the Creator of Redis Squeezed a 284B-Parameter DeepSeek into an Ordinary Laptop
Redis creator antirez built DS4 "Dwarf Star," a pure-C inference engine, using asymmetric quantization to compress DeepSeek V4 Flash from 500GB to 80.8GB for local 128GB unified-memory deployment at 26.7 tokens/sec.
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·3 分钟
The T-Parameter Era of Open-Source LLMs: Four Chinese AI Companies Break the Trillion-Parameter Barrier
Moonshot AI, Alibaba, DeepSeek, and Meituan all crossed the trillion-parameter threshold. China's open-source LLMs made the B-to-T leap in just 18 months.
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·6 分钟
The AI Industrial Age Arrives: Compute Wars, Chip Reconstruction, and the GPT-5.6 Cheating Scandal Explained
Five key AI industry trends: Doubao surpasses 180 trillion daily calls, OpenAI's in-house AI chip, NVIDIA's $3-4 trillion compute forecast, China catching up, and the GPT-5.6 cheating scandal.
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·3 分钟
GPT-5.6 Inference at 18x Speed: OpenAI's Compute Gamble and Business Logic
Why is OpenAI pushing its most powerful model to 750 tokens/s? A deep dive into GPU vs. Cerebras chip cost trade-offs, the $10B compute deal, and how speed, intelligence, and token efficiency are reshaping the AI landscape.
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·3 分钟
LongCat 2.0: Meituan Trains a 1.6 Trillion Parameter LLM on Domestic Chips
Meituan open-sources LongCat 2.0, a 1.6T-parameter MoE model trained on 50,000+ custom chips without NVIDIA GPUs or Google TPUs, rivaling OpenAI and Google.
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·4 分钟
Can Local Models Replace Cloud AI? Five Key Questions That Determine Success or Failure
71% of ChatGPT queries can be handled by local models — but "going local" isn't a one-step move. This guide breaks down the three tiers of local models, license traps, deployment methods, and cost logic to help you find the optimal routing strategy between local and cloud AI.
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·6 分钟
Tencent Hunyuan HY3 Official Version Open-Sourced: The Strongest Under 300B, at 1 Yuan per Million Tokens
Tencent Hunyuan HY3 official version is open-sourced under Apache 2.0, priced as low as 1 yuan per million input tokens, with major gains in agents, reasoning, coding, and long context. On the same day, Meituan open-sourced its trillion-parameter LongCat 2.0.
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·4 分钟
DeepSeek-V4 Deep Dive: Million-Token Context Architecture Breakthrough and Core Innovations
Deep dive into DeepSeek-V4: 1.6T-parameter MoE, CSA+HCA hybrid attention, MHC & MUON optimizer. Inference FLOPs drop to 27% of V3.2, redefining open-source LLM SOTA.
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·5 分钟
DeepSeek Boosts Inference Speed by 85%: How Speculative Decoding Is Reshaping the AI Speed Race
DeepSeek and Peking University's DS Spark paper boosts AI inference speed by up to 85% via confidence scheduling and semi-autoregressive speculative decoding — no model or GPU changes.
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·3 分钟
GPT Flagship Model Integrates with Codex: A Deep Dive into 750 Tokens/sec Inference Speed
OpenAI's top flagship model integrates with Codex, hitting 750 tokens/sec on Cerebras wafer chips. We break down MoE architecture, subscription changes, and open-source advances from Hunyuan and Longcat 2.0.
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·6 分钟
A 284B Model Running on a MacBook: The Real Breakthrough and Barriers of Local DeepSeek Inference
Redis creator runs 284B-parameter DeepSeek model on a MacBook Pro at 26 tokens/sec using a pure C engine, asymmetric quantization, and MoE architecture.
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·1 分钟
Ultimate Review of the Top 10 AI Coding Models: Who Reigns Supreme?
In-depth review of the top 10 AI coding models in 2026, comparing Qwen 3.7 Max, DeepSeek V4 Pro, Claude 4.5 Summit, GPT 5.5 and more across code generation, Agent collaboration, and long-context handling.
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