VRAM
PulseAugur coverage of VRAM — every cluster mentioning VRAM across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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GPU Memory Bandwidth Crucial for Local LLM Speed, Outpacing VRAM
For running large language models locally, GPU memory bandwidth is a more critical factor than VRAM capacity. Higher bandwidth allows the GPU to process data more quickly, preventing it from being bottlenecked while wai…
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Ollama VRAM Guide: 8GB for 7B models, 16GB for 13B, 24GB+ for 34B
This guide details Ollama's VRAM requirements for running various large language models in 2026. It explains that Ollama automatically quantizes models to fit available VRAM, but insufficient memory leads to slow CPU of…
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AI researchers advise against buying more VRAM, suggest optimizing KVCache instead
A social media post suggests that users should stop purchasing more VRAM, advocating instead for techniques like 4-bit quantization and KVCache optimization. The post references models such as Grok and Qwen36 as example…
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Google's Gemma 4 models achieve 3x speed boost with speculative decoding
Google has released Multi-Token Prediction (MTP) drafters for its Gemma 4 open models, which can increase inference speed by up to three times. This advancement utilizes a speculative decoding architecture, allowing a l…