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#llm-serving - page 2 | AI Briefing

Ollama Adds Direct llama.cpp Support

·1·2026.05.14 23:00

Ollama Updates Model Card Information

·2026.05.13 19:00

Ollama Security Vulnerabilities: Memory Leak and RCE Risk

·2026.05.11 14:00

Ultra-fast Inference Engine Atlas Released as Open Source

·2026.05.07 05:00

8x Less Memory Than vLLM, FastDMS Released

·2026.05.05 06:00

Why LLM Serving Needs to Separate CPU and GPU

·2026.05.01 09:00

KV Cache Locality: The Hidden Variable in LLM Serving Costs

·2026.05.01 09:00

Qwen 3.6 Comparison

·2026.04.23 15:00

INT3·INT2 KV Cache Released

·2026.04.22 15:00

Prefill-as-a-Service: Moving Next-Gen Models' KVCache Across Data Centers

·2026.04.20 09:00

Turning on MTP boosts throughput by 24%

·2026.04.18 21:00

2026 vLLM Korea Meetup

·2026.04.14 11:00

4-Chiplet AI SoC With 16Gbps UCIe-Advanced Die-to-Die Interface and Full-Chip Scalable Mesh for Large-Scale AI Inference

·2026.01.02 12:00

OVHcloud Joins Hugging Face as Inference Partner

·2025.11.25 01:00

Hugging Face Adds Public AI as Inference Provider

·2025.09.17 09:00

SGLang integrates Transformers backend

·2025.06.23 09:00

vLLM Improves Long-Prompt Bottleneck Issue

·2025.06.12 17:00

Hugging Face adds support for Featherless AI inference

·2025.06.12 09:00

Request Queuing Strategies for LLM Performance Optimization

·2025.04.02 22:00

Fireworks.ai added as an HF Inference Provider

·2025.02.14 09:00

HF-FriendliAI Model Deployment Integration

·2025.01.22 09:00

TGI Unveils Multi-LoRA Serving Feature

·2024.07.18 09:00

Hugging Face Launches OpenAI-Compatible Messages API

·2024.02.08 09:00

TGI Adds Support for AWS Inferentia2

·2024.02.01 09:00

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