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Qwen 3.5 and Gemma 4 performance measured on MacBook M5

By PulseAugur Editorial · [1 sources] ·

The author conducted performance measurements of Qwen 3.5 and Gemma 4 models on a MacBook M5 with 16 GB of RAM. The analysis included calculations for KV cache and explored how different model sizes, from 8B to 70B parameters, fit within available memory capacities of 16 GB to 128 GB. AI

IMPACT Provides insights into the practical deployment and performance limitations of LLMs on consumer-grade hardware.

RANK_REASON The item details performance measurements and memory capacity analysis for specific LLM models on consumer hardware, fitting the research category. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen 3.5 and Gemma 4 performance measured on MacBook M5

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13 / 100
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The item details performance measurements and memory capacity analysis for specific LLM models on consumer hardware, fitting the research category. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Weights + context + macOS: my measurements of Qwen 3.5 and Gemma 4 on a MacBook M5 16 GB, KV cache math for 8B–70B, and what fits into 16–128 GB. # ai # llm # m

    Weights + context + macOS: my measurements of Qwen 3.5 and Gemma 4 on a MacBook M5 16 GB, KV cache math for 8B–70B, and what fits into 16–128 GB. # ai # llm # macos # machinelearning # software # coding # development # engineering # inclusive # community How much RAM does a local…

    LINKS dev.to/…/how-much-ram-does-a-local-llm-ne…

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