#speculative decoding performance
144 related articles
·3 min
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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·3 min
Kimi K3 Reaches 2.5T Parameters, MiniMax M3 Pro Brewing Simultaneously: China's LLM Arms Race Escalates
Kimi K3 adopts new architecture with 2.5T parameters and 1M token context. MiniMax M3 Pro targets 2.7-3T. OpenAI surpasses 7M users, HY-OCR 1.5 achieves SOTA, Amap launches world model.
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·2 min
Kimi 3 Added to Pro Subscription: Accelerating Commercialization of Chinese LLMs
Kimi 3 joins the Pro subscription plan, giving paying users direct access to the latest flagship model. Analysis of Kimi 3's upgrades, Moonshot AI's subscription strategy, and China's evolving LLM landscape.
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·2 min
Kimi 3 Included in Pro Subscription: Accelerating Commercialization of Chinese LLMs
Kimi 3 is now included in the Pro subscription plan, giving paying users direct access to the latest flagship model. This article analyzes Kimi 3's upgrades, Moonshot AI's subscription strategy, and shifts in China's LLM competitive landscape.
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·4 min
Cursor Start India Plan at ₹649/Month: Decoding the Regional Pricing Strategy for AI Coding Tools
Cursor launches its Start plan for India at ₹649/month (~$7.70), featuring Grok 4.5 and Composer Agent. A deep dive into the PPP pricing strategy and its market implications.
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·4 min
Colibri: Running a 744-Billion-Parameter LLM on an Ordinary Laptop
Colibri uses MoE hot-cold separation and 4-bit quantization to run 744B-parameter models like GLM 5.2 on consumer hardware. Learn about its three-tier memory architecture and speculative decoding.
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·4 min
Laguna S 2.1 Deep Dive: Hands-On Local Deployment of a 118B Parameter Coding Model
In-depth review of Poolside's Laguna S 2.1 open-source coding model: MoE architecture, RL training, DGX Spark local deployment, and real-world agentic coding tests with 8B active parameters.
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·3 min
Claude Opus 5 Officially Released: Performance Approaching the Top Tier as the Open-Weight Debate Heats Up Again
Anthropic releases Claude Opus 5 with near-frontier performance at lower prices. Same day, Jensen Huang co-signs open-weight letter with 20+ companies while DeepSeek fundraising rumors surface.
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·3 min
Opus 5 Hands-On: Powerful but Slow — Inference Speed Becomes the New AI Battleground
An AI practitioner tests Opus 5: powerful capabilities but painfully slow inference. Deep analysis of how LLM competition is shifting from intelligence to inference speed.
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·3 min
D-Flash: The Secret Behind 3.5x LLM Inference Speedup with Diffusion Drafting
D-Flash uses fast diffusion parallel drafting and target feature KV injection to solve the autoregressive Drafter latency bottleneck in speculative decoding. 16 tokens in just 6ms, up to 3.5x speedup on HumanEval, surpassing EAGLE3 and MTP.
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·2 min
D-Flash: How Diffusion Drafting Delivers 3.5x Faster LLM Inference
D-Flash solves the autoregressive drafter latency bottleneck in speculative decoding via fast diffusion parallel drafting and target feature KV injection. 16 tokens in just 6ms, up to 3.5x speedup on HumanEval, beating EAGLE3 and MTP.
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·3 min
Laguna S 2.1: The Open-Source Coding Model That's 14x Smaller Yet Stronger
Poolside releases Laguna S 2.1, an open-source agentic coding model: 118B total params with only 8B active, scoring 40.4% on DeepSWE — ~4.5x DeepSeek V4 Pro Max. Supports 1M-token context, deployable on a single workstation.
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·3 min
DeepSeek Open-Sources DeepSpec: A Full-Stack Speculative Decoding Library with 60–85% Inference Speedup
DeepSeek open-sources DeepSpec, a full-stack speculative decoding library delivering 60–85% inference speedup and up to 661% throughput gains in production. MIT license, 9 checkpoints, 9 benchmarks.
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·5 min
Why Are China's Open-Source AI Models Getting Stronger? A Deep Dive into Three Comeback Paths
Facing US chip bans and closed-source monopolies, how do China's open-source AI models keep striking back? A deep dive into three core paths: open-source pricing-power games, optical interconnect positioning, and edge-side use cases.
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·5 min
Why Are China's Open-Source AI Models Getting Stronger? A Deep Dive Into Three Comeback Strategies
Facing US chip bans and closed-source monopoly, how do China's open-source AI models keep fighting back? A deep dive into three core paths: open-source pricing games, optical interconnect positioning, and on-device scenarios.
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·3 min
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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·3 min
The Rise of General AI: Breakthroughs in Mathematical Reasoning and Competitive Programming
Frontier AI is going general: costs are dropping, general models are beating specialized ones in math and competitive programming, and multi-agent workflows are maturing fast.
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·3 min
Is Gemini Getting Worse? A Deep Dive into the 'Model Degradation' Phenomenon
Reddit users report Gemini feeling "worse over time." This deep dive explains the real causes—silent updates, safety over-alignment, and compute throttling—plus how to rationally evaluate AI model performance.
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·7 min
Auditing Cryptographic Libraries with AI: What We Found in Cloudflare's CIRCL
An in-depth look at using AI LLMs to audit Cloudflare's open-source cryptographic library CIRCL, covering constant-time detection, side-channel vulnerabilities, and human-AI collaboration.
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·6 min
Hands-On with Panel AI On-Premises Deployment: One-Click Enterprise Adoption and Unified Compute Cluster Scheduling
In-depth review of Panel AI v1.1.1: second-level installation, no-public-IP networking, batch compute cluster management. Learn how enterprise AI on-premises deployment barriers are dramatically lowered.
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