Skip to main content
株式会社オブライト
Services
About
Company
Column
Glossary
Pricing
Free Tools
Contact
日本語
日本語
メニューを開く
Column
GPU
Articles tagged "GPU"
7 articles
AI
2026-09-06
AMD Threadripper Halo Station Explained: 96-Core CPU, 576GB HBM3E AI Workstation (Sept 2026)
AMD's Threadripper Halo Station: 96-core CPU, 4 MI350P GPUs, 576GB HBM3E, 16TB/s bandwidth, targets trillion-param models at 4-bit. Price, date unannounced.
AI
ローカルLLM
VRAM
AI
2026-08-31
Local LLM Context Length and VRAM: KV Cache Formula Guide
Local LLM OOM errors usually come from the KV cache, not model weights, because it grows linearly with context length. Formula, sizing table and fixes.
VRAM
ローカルLLM
MoE
Software Development
2026-08-21
Mojo Goes Fully Open Source Under Apache 2.0: What Changes
On Aug 18, 2026, Modular open sourced the Mojo compiler, toolchain, stdlib under Apache 2.0 with LLVM exceptions: scope, build steps, open contributions.
Mojo
開発ツール
オープンソース
Software Development
2026-08-12
Mojo 1.0 Is Here: Install, GPU Support, and vs Python
In August 2026, Modular released Mojo 1.0. Learn what it is, how to install it, supported OS/GPU setups, and how it differs from Python, Rust, C++, and CUDA.
Mojo
開発ツール
オープンソース
AI
2026-05-25
Gemma 4 System Requirements — 5–62GB VRAM, RTX 3060 to H100 by Variant (E2B/E4B/26B/31B) [2026 Guide]
Gemma 4 needs 5GB VRAM (E2B/E4B), 16GB (26B MoE), or 24-62GB (31B Dense) depending on quantization. Requirements by model: RTX 3060 to H100, Apple Silicon M1-M4, CPU-only operation, RAM sizing, and budget builds. Updated July 2026.
Gemma 4
ハードウェア
GPU
AI
2026-05-05
NVIDIA DGX Spark in 2026 — A Two-Stage Workflow for Code Migrations Where "Confidential Analysis Stays Local, Cloud LLMs Only Touch Sanitized Code"
An overview of NVIDIA DGX Spark (GB10 Grace Blackwell Superchip, 128GB unified memory, up to 1 PFLOP at FP4, $4,699) and a concrete two-stage workflow for confidential code-migration projects: analyze and sanitize locally, then hand a clean, PII-free representation to cloud frontier LLMs for the actual migration. Practical answers to the "executives won't approve cloud AI even with opt-out" problem.
NVIDIA
DGX Spark
ローカルLLM
AI
2026-03-17
Practical Guide to Deploying Rakuten AI 3.0 from Hugging Face
A detailed guide to downloading Rakuten's latest LLM 'Rakuten AI 3.0' from Hugging Face and building inference environments with vLLM and TGI. Practical coverage from MoE model-specific GPU memory requirements, quantization for optimization, API server construction, to production deployment best practices.
Rakuten AI 3.0
Hugging Face
デプロイ