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Research Paper
Research Paper
I reference the DeepSeek V3 technical report because it’s the cleanest source for understanding what’s actually new: MoE routing, MLA, MTP, and the FP8 cost story. If you want to build GenAI systems (RAG/agents) with the right trade-offs, reading the paper alongside real benchmarks is the fastest way to avoid cargo-culting.
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Pros
- +Primary source for DeepSeek V3 architecture and training details
- +Clarifies why MoE + attention efficiency changes deployment economics
- +Useful for system-design level takeaways, not just benchmarks
Cons
- -Dense and technical if you’re new to MoE/attention internals
- -May not answer all dataset/provenance questions people ask
![What is DeepSeek? [Technical Report Explained] | Multi-Head Latent Attention | Mixture of Experts](https://img.youtube.com/vi/0sW-oWuHxX4/mqdefault.jpg)