Dee1 (Deevervee Dee1)
Category:
Frontier Foundation Model
Client:
AGI Supported. First-generation 300B-parameter sparse Mixture-of-Experts (MoE) flagship model.
Duration:
November 20, 2026 (Q4 2026)
Dee1 is Deevo’s frontier-scale foundational intelligence engine, structured as a 300-billion-parameter sparse Mixture-of-Experts (MoE) network that redefines computational efficiency at scale. Rather than activating its entire parameter volume on every forward pass, Dee1 routes incoming tokens through top-k gating routers to dynamically activate approximately 38 billion parameters per token. This architectural paradigm delivers the reasoning breadth and associative memory of a dense 300B model while operating at the latency and inference cost of a radically smaller network.
Trained across dense superclusters utilizing 3D parallelism (Megatron-LM sequence, tensor, and pipeline sharding), Dee1’s parameter space is partitioned into dozens of specialized feed-forward expert pathways. Each expert develops deep domain specialization across computational mathematics, kernel development, formal logic verification, and multi-modal scene synthesis. Shared latent experts run in parallel across every token, preserving unified conceptual coherence and preventing fragmentation across distributed expert nodes.
Dee1 incorporates speculative decoding and hardware-fused routing kernels written in OpenAI Triton, enabling it to achieve sub-14ms time-to-first-token latencies in production environments. Its native multi-modal ingestion layers process heterogeneous data streams—including high-resolution visual inputs, AST syntax trees, and continuous telemetry signals—within a unified embedding space. This allows the model to reason across abstract architectural diagrams, raw code, and mathematical formulations simultaneously without requiring intermediate modality translation.
Engineered to serve as the core intelligence engine for Deevo’s enterprise ecosystem, Dee1 exhibits state-of-the-art deductive performance on advanced code generation, competitive mathematical theorems, and multi-hop logical deductions. Its training regimen utilized our advanced curricular token sequencing, pairing synthetic reasoning paths with formal verifier feedback loops. Dee1 stands as our benchmark foundation model, powering the entire suite of Deevo Universe autonomous workflows and high-concurrency systems.




