DeepSeek Coder V2 demonstrates notable performance on the Intel N100, particularly in coding tasks, when compared to other CPUs.
The Intel N100, equipped with four cores and capable of reaching a maximum clock speed of 3.4 GHz for dual-core tasks, exhibits varying performance based on the number of cores utilized. For instance, while it can achieve 3.4 GHz in single-core tasks, its all-core performance peaks at around 2.9 GHz. This characteristic makes it less powerful in multi-threaded scenarios but still competitive for applications that can leverage its single-core capabilities effectively[1].
In practical tests, users have reported that DeepSeek Coder V2 runs efficiently on the N100, outperforming other models like Llama3 and CodeGemma significantly in terms of speed and usability of generated code. One user noted that it ran at least twice as fast as Llama3:7b and produced readily usable code without extensive modifications, which is a significant advantage for developers seeking efficiency[5]. The model's architecture, a Mixture-of-Experts (MoE), allows it to handle complex coding tasks effectively, even on hardware without dedicated GPUs[6][7].
Comparatively, while more powerful CPUs may provide better overall performance for demanding applications or larger models, the Intel N100's ability to run DeepSeek Coder V2 efficiently highlights its suitability for specific coding tasks where single-threaded performance is prioritized. Users have found that despite its limitations in multi-core processing, the N100 still delivers impressive results with the model, making it a viable option for those working within its constraints[2][4].
Citations:
[1] https://www.youtube.com/watch?v=7YbHAblcQrk
[2] https://dataloop.ai/library/model/bartowski_deepseek-coder-v2-instruct-gguf/
[3] https://www.youtube.com/watch?v=LVSA-GtITb0
[4] https://arxiv.org/html/2406.11931v1
[5] https://www.reddit.com/r/LocalLLaMA/comments/1dkmpja/impressive_performance_of_deepseekcoderv216b_on/
[6] https://blog.promptlayer.com/deepseek-v2-vs-coder-v2-a-comparative-analysis/
[7] https://artificialanalysis.ai/models/deepseek-coder-v2
[8] https://github.com/vllm-project/vllm/issues/6655