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DeepSeek-V3 is a large language model released by the Chinese AI company DeepSeek in late 2024. It is built as a Mixture-of-Experts (MoE) model with a total of 671 billion parameters, of which only 37 billion are activated per token. The model was trained efficiently using a specialized architecture...
DeepSeek-Coder-V2 is an open-weights language model designed for advanced code generation. Developed by Continue.AI, it leverages a CodeGen-UvLM architecture and incorporates Mixture of Experts (MoE) technology to improve performance. This model is particularly useful for developers, software engine...
Databricks' open mixture-of-experts language model released in March 2024 with 132B total parameters (36B active per token), setting open-source MoE performance records at launch.
Mixtral is famous for its Mixture-of-Experts (MoE) architecture, allowing it to achieve performance rivaling much larger models while maintaining reasonable inference speeds when self-hosted. Running this model locally provides a massive boost in coding assistance, especially for understanding compl...
Mixtral provides massive effective parameter count and superior context handling due to its Mixture-of-Experts (MoE) architecture. This makes it phenomenal for understanding very large codebases or complex architectural patterns. However, it demands substantial VRAM, placing it in the advanced tier...
Phi-3.5-MoE is a mixture-of-experts language model from Microsoft (2024), with 16 experts and roughly 6.6 billion active parameters, offering strong reasoning relative to its compute cost.
Mixtral 8x7B is a Mixture-of-Experts (MoE) model known for its massive context window and superior general reasoning. While not exclusively a coding model, its sheer intelligence makes it exceptional for tasks requiring deep understanding of surrounding files or complex architectural discussions. Wh...
