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llama.cpp outperforms Ollama in Gemma4:e2B speed test

By PulseAugur Editorial · [1 sources] ·

A comparison between llama.cpp and Ollama shows that llama.cpp is faster when running the Gemma4:e2B model. llama.cpp achieved a generation rate of 12.5 tokens/s, while Ollama's evaluation rate was 10.17 tokens/s. This speed difference aligns with general reports of llama.cpp offering a 20%-25% speed improvement. AI

IMPACT llama.cpp offers a performance advantage over Ollama for local LLM deployment.

RANK_REASON Comparison of two software tools for running LLMs.

Read on Mastodon — sigmoid.social →

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

llama.cpp outperforms Ollama in Gemma4:e2B speed test

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Comparison of two software tools for running LLMs.
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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    A quick and dirty comparison of llama.cpp with ollama. The model used is `gemma4:e2b` and the prompt is a simple 'hi'. Thinking mode is on. Running the direct C

    A quick and dirty comparison of llama.cpp with ollama. The model used is `gemma4:e2b` and the prompt is a simple 'hi'. Thinking mode is on. Running the direct CLI mode for both. * llama.cpp: `Generation: 12.5 t/s` * ollama: `eval rate: 10.17 tokens/s` This matches the expect 20%-…

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