The performance of DeepSeek Coder V2 varies significantly with different CPU models, primarily influenced by the architecture and specifications of the CPUs used.
**Speed and Efficiency
DeepSeek Coder V2 is designed to be highly efficient, allowing it to process large codebases quickly. On CPUs with higher core counts and better architecture, such as those with 64 ARM cores, the model can achieve impressive throughput rates, reportedly around 17 tokens per second (tps) when using optimized quantizations like IQ_4_XS[5]. In contrast, running the model on lower-end CPUs, such as the Intel N100, yields slower performance, although users have reported it running at least twice as fast as other models like Llama3 on similar hardware[3].
**Impact of Quantization
The model's performance is also heavily dependent on the chosen quantization type. Higher quality quantizations (e.g., Q8_0) provide better accuracy but require more computational resources. Conversely, lower quality options (e.g., Q2_K) can still deliver usable results but may compromise on speed and accuracy[2]. Users have found that selecting a quantization that fits within the available VRAM of their GPU can lead to optimal performance, particularly for those utilizing hybrid CPU-GPU setups[2].
**Benchmark Comparisons
In benchmark evaluations, DeepSeek Coder V2 has demonstrated superior performance compared to closed-source models like GPT-4 Turbo and Claude 3 in coding tasks[1][7]. This suggests that the model's architecture is well-optimized for various CPU configurations, although specific performance metrics can vary widely based on the hardware capabilities.
Overall, while DeepSeek Coder V2 shows robust performance across different CPU models, its effectiveness is maximized with higher-end CPUs that support advanced architectures and optimal quantization strategies.
Citations:
[1] https://dataloop.ai/library/model/deepseek-ai_deepseek-coder-v2-instruct/
[2] https://dataloop.ai/library/model/bartowski_deepseek-coder-v2-lite-instruct-gguf/
[3] https://www.reddit.com/r/LocalLLaMA/comments/1dkmpja/impressive_performance_of_deepseekcoderv216b_on/
[4] https://stratechery.com/2025/deepseek-faq/
[5] https://huggingface.co/nisten/deepseek-coder-v2-inst-cpu-optimized-gguf
[6] https://arxiv.org/html/2412.19437v1
[7] https://arxiv.org/abs/2406.11931
[8] https://blog.promptlayer.com/deepseek-v2-vs-coder-v2-a-comparative-analysis/