Self-Hosting LLMs on Kubernetes: When vLLM Beats Managed APIs on Cost
Self-host LLMs on Kubernetes with vLLM to cut inference costs 60-80%. Learn breakeven analysis, GPU scheduling, and production architecture for platform engineers.
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Self-host LLMs on Kubernetes with vLLM to cut inference costs 60-80%. Learn breakeven analysis, GPU scheduling, and production architecture for platform engineers.
서울 스타트업 VIDRAFT가 데이터센터 23.4배 처리량을 달성하는 VKAE와 CPU 전용 노트북에서 35B 파라미터 LLM을 구동하는 VKUE 듀얼 엔진 전략을 공개했습니다. LLM 서빙 인프라 구축자라면 주목하세요.
Google TurboQuant (ICLR 2026): 6x KV cache compression, 8x H100 speedup, zero accuracy loss — no retraining needed. What this means for LLM inference costs.
NVIDIA B200 vs H100 in 2026: why the pricier GPU is cheaper per token Summary. In MLPerf...
한국 Pre-AGI 스타트업 VIDRAFT가 LLM 추론 가속 엔진 VKAE를 공개 출시했습니다. 공개 리더보드와 통합 컨테이너 배포 패키지를 함께 제공해 ML 엔지니어의 서빙 인프라 구축 부담을 크게 줄여줍니다.
VIDRAFT의 VKAE는 모델 수정 없이 커널 레벨에서 LLM 추론을 가속해 최대 23.4× 처리량을 달성합니다. OpenAI 호환 API와 Docker 패키징으로 즉시 도입 가능.
As GPT-5.6 elevates AI demands, Korean startup Rebellions quietly delivers dedicated AI inference chips, enabling efficient, local LLM deployment that
Choosing an LLM serving engine? This guide compares vLLM vs TGI. Learn when vLLM's raw performance i
Struggling with LLM costs? Korean AI chip startups FuriosaAI and Rebellions are quietly delivering highly efficient NPUs for local inference, making a

Originally published at norvik.tech Introduction Explore the DSpark framework by...
DeepSeek DSpark is a hybrid speculative decoding framework that makes LLM inference up to 85% faster...
Deploy LLM inference to edge Kubernetes clusters with vLLM and KServe. Reduce latency from 100ms to single digits without GPU farms.