404Dev: CodeBase-280B Performance Boosts
⚡ Performance & Efficiency
- Only a fraction of the model’s parameters are active at a time for each token
- Parallel attention and MoE pathways maximize GPU usage
- Sparse activation + quantized caches drastically reduces memory requirements
🔮 Future Plans
- Faster attention with FlashAttention
- Expert parallelism across devices
- Advanced quantization methods (GPTQ, AWQ)
- Pipeline parallelism and gradient checkpointing for huge-scale models
We’re thrilled to see what the community can do with CodeBase-280B and can’t wait to continue development in the coming months.
- Conner | 404Development
