Mnemic steers MoE routers at inference time

Hot take: if even a fraction of this holds up outside the author’s own benchmarks, it’s a legitimately new inference-time control surface for MoE models rather than just another memory/RAG wrapper.

• –The repo explicitly positions Mnemic as zero-training, zero-weight-modification runtime knowledge assimilation for MoE systems, with `mnemic-mre` published on GitHub and PyPI-style install instructions.
• –The strongest claim is not “better retrieval,” but “route the model into the right experts,” which is interesting because it leans on architecture already present in the base model.
• –The current evidence base is thin: the README says alpha, the tests are mostly on Gemma 4 26B, and the demo claims are self-reported, so replication by third parties matters a lot.
• –The product feels most plausible as a research-to-tooling bridge for MoE experimentation, not as a drop-in universal knowledge layer yet.