Expired90% confidenceFactTime unknown
The hardware used for testing was a Mac Studio equipped with 96 GB of memory and an M2 Max chip, with Ollama as the deployment tool.
1
Sources
90%
Confidence
Medium-term (~90 days)
Relevance
6/1/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 8/30/2026(expired)
Sources
Related Entities
Related Claims
UnverifiedMac Studio models equipped with M2 Ultra or M3 Ultra chips can be configured with up to 192GB of unified memory, with the CPU and GPU sharing the same memory pool.79% similarUnverifiedA Mac Studio M4 Ultra equipped with 192 GB of unified memory can theoretically run complete 70B or even larger parameter models.74% similarUnverifiedOllama uses model quantization techniques (such as 4-bit and 8-bit quantization) to enable consumer-grade hardware (such as a MacBook with 16GB of memory) to run models with billions of parameters.74% similarUnverifiedThe 4-bit quantized GGUF format version of llama.cpp enables the Llama 3.1 70B model to run on an Apple M2 Ultra with 64GB unified memory at an inference speed of approximately 20–30 tokens/second.71% similar
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