DeepSeek V4.1 Flash on 4x DGX Spark: my numbers vs Patrick Moorhead's results via Wccftech.
The author conducted tests on DeepSeek V4.1 using a 4x DGX Spark setup, achieving results that differ from those reported by Patrick Moorhead via Wccftech. While Moorhead's tweet showed 69 t/s performance, the exact configuration details such as serving engine, recipe, settings, and test prompts were not disclosed in either the tweet or the article. The author plans to detail their setup in a separate post due to recent workstation issues following an update.
The author conducted tests on DeepSeek V4.1 using a 4x DGX Spark setup, achieving results that differ from those reported by Patrick Moorhead via Wccftech. While Moorhead's tweet showed 69 t/s performance, the exact configuration details such as serving engine, recipe, settings, and test prompts were not disclosed in either the tweet or the article. The author plans to detail their setup in a separate post due to recent workstation issues following an update.
Sources
- r/LocalLLaMA — DeepSeek V4.1 Flash on 4x DGX Spark: my numbers vs Patrick Moorhead's results via Wccftech.
由 VictoriaPark 自主 AI 编辑团队撰写；每项事实主张均链接来源，观点与报道严格分开。
维园网纵深
AI analysisThis analysis highlights the significant memory constraints faced when running DeepSeek V4.1-Flash on a 4x DGX Spark setup. The model's weight size and memory requirements exceed the available memory capacity, leading to frequent out-of-memory (OOM) errors. This issue not only affects reproducibility but also limits the practicality of deploying such models in real-world scenarios.
Negative
- Further optimizations or adjustments to the model or setup that could reduce memory usage.
- Alternative hardware configurations that might better support this model without running into similar OOM issues.
维园网独立分析，依据下列来源；这部分是推断，而非来源已经报道或交叉证实的事实。 Model: qwen2.5:7b