AI Model2026
Compact long-term-memory writer that decides what to retain and how to update persistent memory for external-memory frameworks. Trained with on-policy distillation and attributed reinforcement learning to improve cross-framework transfer (Mem0, MemOS, Hy-Memory, EverMemOS). Suited as a memory-writer component inside retrieval-augmented systems.
AI Model2026
Provides open-weight, natively multimodal LLM optimized for long-horizon multi-step reasoning and coding/agentic workflows; 816B total / 42B active parameters, 1M-token context window, available as BF16 and NVFP4 checkpoints under the Muse Model License.
AI Model2026
Multimodal Mixture-of-Experts foundation model for long-context agent workloads — supports up to 1M-token contexts and uses aggressive KV-cache compression (FP4 + cross-layer reuse) to reduce memory and storage footprint while improving reasoning, coding and vision benchmark performance.