Unified Memory
4 posts tagged #unified-memory
4 posts on Unified Memory, all in the Local LLM Hardware pillar — most read: “Apple Silicon vs NVIDIA GPU for Local LLMs” and “ZGX Fury LLM Benchmark: The 3,000 Tok/s Claim Explained”.
AI and Machine Learning ZGX Fury LLM Benchmark: The 3,000 Tok/s Claim Explained
A viral video says the ZGX Fury hits 3,000 tokens/sec locally. Here's what that number means, how it compares to RTX 5090 and Mac Studio, and the setup gotchas to plan for.
AI and Machine Learning M4 Max vs M5 Max for Local AI: Which Should You Buy?
The M5 Max wins for serious local AI workloads, with 614GB/s of memory bandwidth against the M4 Max's 546GB/s and a Neural Accelerator in every GPU core. The M4 Max remains the smart buy for budget-conscious developers who don't need the extra speed.
AI and Machine Learning Apple Silicon vs NVIDIA GPU for Local LLMs
NVIDIA wins on raw throughput and ecosystem depth for serious multi-GPU workloads; Apple Silicon wins on memory bandwidth per dollar and zero-friction local inference for solo developers. Your budget and batch size decide the rest.
AI and Machine Learning Apple M4 vs M4 Max for Local LLMs: Which Should You Buy?
The M4 Max wins for serious local LLM work thanks to its unified memory ceiling and bandwidth advantage; the base M4 wins for portability and budget-conscious inference on smaller models. Here's exactly where the line falls.
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